Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology
Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Jagaba, Ahmad Hussaini [verfasserIn] Lawal, Ibrahim Mohammed [verfasserIn] Ghfar, Ayman A. [verfasserIn] Usman, Abdullahi Kilaco [verfasserIn] Yaro, Nura Shehu Aliyu [verfasserIn] Noor, Azmatullah [verfasserIn] Abioye, Kunmi Joshua [verfasserIn] Birniwa, Abdullahi Haruna [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Chemosphere - Amsterdam [u.a.] : Elsevier Science, 1972, 339 |
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| Übergeordnetes Werk: |
volume:339 |
| DOI / URN: |
10.1016/j.chemosphere.2023.139620 |
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| Katalog-ID: |
ELV061954691 |
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| 245 | 1 | 0 | |a Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology |
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| 520 | |a Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40–100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities. | ||
| 650 | 4 | |a Biochar | |
| 650 | 4 | |a Biorefinery wastewater | |
| 650 | 4 | |a Geopolymer nanocomposite | |
| 650 | 4 | |a Phenol | |
| 650 | 4 | |a Response surface methodology | |
| 650 | 4 | |a Extended aeration system | |
| 700 | 1 | |a Lawal, Ibrahim Mohammed |e verfasserin |4 aut | |
| 700 | 1 | |a Ghfar, Ayman A. |e verfasserin |4 aut | |
| 700 | 1 | |a Usman, Abdullahi Kilaco |e verfasserin |4 aut | |
| 700 | 1 | |a Yaro, Nura Shehu Aliyu |e verfasserin |4 aut | |
| 700 | 1 | |a Noor, Azmatullah |e verfasserin |0 (orcid)0000-0002-0241-8764 |4 aut | |
| 700 | 1 | |a Abioye, Kunmi Joshua |e verfasserin |4 aut | |
| 700 | 1 | |a Birniwa, Abdullahi Haruna |e verfasserin |4 aut | |
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10.1016/j.chemosphere.2023.139620 doi (DE-627)ELV061954691 (ELSEVIER)S0045-6535(23)01887-8 DE-627 ger DE-627 rda eng 333.7 VZ 43.00 bkl Jagaba, Ahmad Hussaini verfasserin aut Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40–100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities. Biochar Biorefinery wastewater Geopolymer nanocomposite Phenol Response surface methodology Extended aeration system Lawal, Ibrahim Mohammed verfasserin aut Ghfar, Ayman A. verfasserin aut Usman, Abdullahi Kilaco verfasserin aut Yaro, Nura Shehu Aliyu verfasserin aut Noor, Azmatullah verfasserin (orcid)0000-0002-0241-8764 aut Abioye, Kunmi Joshua verfasserin aut Birniwa, Abdullahi Haruna verfasserin aut Enthalten in Chemosphere Amsterdam [u.a.] : Elsevier Science, 1972 339 Online-Ressource (DE-627)306354217 (DE-600)1496851-4 (DE-576)081952961 1879-1298 nnns volume:339 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 339 |
| spelling |
10.1016/j.chemosphere.2023.139620 doi (DE-627)ELV061954691 (ELSEVIER)S0045-6535(23)01887-8 DE-627 ger DE-627 rda eng 333.7 VZ 43.00 bkl Jagaba, Ahmad Hussaini verfasserin aut Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40–100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities. Biochar Biorefinery wastewater Geopolymer nanocomposite Phenol Response surface methodology Extended aeration system Lawal, Ibrahim Mohammed verfasserin aut Ghfar, Ayman A. verfasserin aut Usman, Abdullahi Kilaco verfasserin aut Yaro, Nura Shehu Aliyu verfasserin aut Noor, Azmatullah verfasserin (orcid)0000-0002-0241-8764 aut Abioye, Kunmi Joshua verfasserin aut Birniwa, Abdullahi Haruna verfasserin aut Enthalten in Chemosphere Amsterdam [u.a.] : Elsevier Science, 1972 339 Online-Ressource (DE-627)306354217 (DE-600)1496851-4 (DE-576)081952961 1879-1298 nnns volume:339 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 339 |
| allfields_unstemmed |
10.1016/j.chemosphere.2023.139620 doi (DE-627)ELV061954691 (ELSEVIER)S0045-6535(23)01887-8 DE-627 ger DE-627 rda eng 333.7 VZ 43.00 bkl Jagaba, Ahmad Hussaini verfasserin aut Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40–100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities. Biochar Biorefinery wastewater Geopolymer nanocomposite Phenol Response surface methodology Extended aeration system Lawal, Ibrahim Mohammed verfasserin aut Ghfar, Ayman A. verfasserin aut Usman, Abdullahi Kilaco verfasserin aut Yaro, Nura Shehu Aliyu verfasserin aut Noor, Azmatullah verfasserin (orcid)0000-0002-0241-8764 aut Abioye, Kunmi Joshua verfasserin aut Birniwa, Abdullahi Haruna verfasserin aut Enthalten in Chemosphere Amsterdam [u.a.] : Elsevier Science, 1972 339 Online-Ressource (DE-627)306354217 (DE-600)1496851-4 (DE-576)081952961 1879-1298 nnns volume:339 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 339 |
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10.1016/j.chemosphere.2023.139620 doi (DE-627)ELV061954691 (ELSEVIER)S0045-6535(23)01887-8 DE-627 ger DE-627 rda eng 333.7 VZ 43.00 bkl Jagaba, Ahmad Hussaini verfasserin aut Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40–100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities. Biochar Biorefinery wastewater Geopolymer nanocomposite Phenol Response surface methodology Extended aeration system Lawal, Ibrahim Mohammed verfasserin aut Ghfar, Ayman A. verfasserin aut Usman, Abdullahi Kilaco verfasserin aut Yaro, Nura Shehu Aliyu verfasserin aut Noor, Azmatullah verfasserin (orcid)0000-0002-0241-8764 aut Abioye, Kunmi Joshua verfasserin aut Birniwa, Abdullahi Haruna verfasserin aut Enthalten in Chemosphere Amsterdam [u.a.] : Elsevier Science, 1972 339 Online-Ressource (DE-627)306354217 (DE-600)1496851-4 (DE-576)081952961 1879-1298 nnns volume:339 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 339 |
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10.1016/j.chemosphere.2023.139620 doi (DE-627)ELV061954691 (ELSEVIER)S0045-6535(23)01887-8 DE-627 ger DE-627 rda eng 333.7 VZ 43.00 bkl Jagaba, Ahmad Hussaini verfasserin aut Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40–100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities. Biochar Biorefinery wastewater Geopolymer nanocomposite Phenol Response surface methodology Extended aeration system Lawal, Ibrahim Mohammed verfasserin aut Ghfar, Ayman A. verfasserin aut Usman, Abdullahi Kilaco verfasserin aut Yaro, Nura Shehu Aliyu verfasserin aut Noor, Azmatullah verfasserin (orcid)0000-0002-0241-8764 aut Abioye, Kunmi Joshua verfasserin aut Birniwa, Abdullahi Haruna verfasserin aut Enthalten in Chemosphere Amsterdam [u.a.] : Elsevier Science, 1972 339 Online-Ressource (DE-627)306354217 (DE-600)1496851-4 (DE-576)081952961 1879-1298 nnns volume:339 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 339 |
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Biochar Biorefinery wastewater Geopolymer nanocomposite Phenol Response surface methodology Extended aeration system |
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Jagaba, Ahmad Hussaini @@aut@@ Lawal, Ibrahim Mohammed @@aut@@ Ghfar, Ayman A. @@aut@@ Usman, Abdullahi Kilaco @@aut@@ Yaro, Nura Shehu Aliyu @@aut@@ Noor, Azmatullah @@aut@@ Abioye, Kunmi Joshua @@aut@@ Birniwa, Abdullahi Haruna @@aut@@ |
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2023-01-01T00:00:00Z |
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Jagaba, Ahmad Hussaini |
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Jagaba, Ahmad Hussaini ddc 333.7 bkl 43.00 misc Biochar misc Biorefinery wastewater misc Geopolymer nanocomposite misc Phenol misc Response surface methodology misc Extended aeration system Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology |
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333.7 VZ 43.00 bkl Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology Biochar Biorefinery wastewater Geopolymer nanocomposite Phenol Response surface methodology Extended aeration system |
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Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology |
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Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology |
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Jagaba, Ahmad Hussaini Lawal, Ibrahim Mohammed Ghfar, Ayman A. Usman, Abdullahi Kilaco Yaro, Nura Shehu Aliyu Noor, Azmatullah Abioye, Kunmi Joshua Birniwa, Abdullahi Haruna |
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biochar-based geopolymer nanocomposite for cod and phenol removal from agro-industrial biorefinery wastewater: kinetic modelling, microbial community, and optimization by response surface methodology |
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Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology |
| abstract |
Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40–100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities. |
| abstractGer |
Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40–100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities. |
| abstract_unstemmed |
Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40–100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities. |
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Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008–0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. 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| score |
7.4005013 |