Biological pre-hydrolysis and thermal pretreatment applied for anaerobic digestion improvement: Kinetic study and statistical variable selection

•Biological prehydrolysis and thermal treatment were used to improve anaerobic digestion.•The higher methane yield was reached at BPH 37 °C for 20 h followed 55 °C for 20 h.•Statistical study allowed us four essential variables to modeling methane yield.•Predicted methane yield was close to experime...

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Veröffentlicht in:Cleaner Waste Systems Jg. 2; S. 100005
Hauptverfasser: El Gnaoui, Y., Frimane, A., Lahboubi, N., Herrmann, C., Barz, M., EL Bari, H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.07.2022
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ISSN:2772-9125, 2772-9125
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Zusammenfassung:•Biological prehydrolysis and thermal treatment were used to improve anaerobic digestion.•The higher methane yield was reached at BPH 37 °C for 20 h followed 55 °C for 20 h.•Statistical study allowed us four essential variables to modeling methane yield.•Predicted methane yield was close to experimental, which validates the models used. [Display omitted] In the present study, two pretreatment methods (thermal pretreatment and biological pre-hydrolysis) were suggested for food waste (FW) with the aim to enhance biomass conversion and biogas production by anaerobic. The effects of thermal pretreatment (TP), including TP at 60 °C and 80 °C for 60 min, and TP at 100 °C, 120 °C and 140 °C for 30 min, well as biological pre-hydrolysis (BPH) at 37 °C, 55 °C, 37 °C followed by 55 °C and 55 °C followed by 37 °C for 40 h on anaerobic digestion performance of FW were evaluated in batch tests. Results were compared with untreated FW. The BPH and TP caused an increase in the soluble chemical oxygen demand and hydrolysis efficiency. The methane yield (MY) increased from 371.17 mL CH4/g VS for untreated FW to 471.95 mL CH4/ g VS. The maximal MY was recorded for BPH at 37 °C for 20 h followed by 55 °C for 20 h. The pretreatments increased the biogas production rate and reduced the lag phase. The most influential variables on the methane yield were investigated using three statistical methods: Principal component analysis, Mutual Information and R-squared. The results allowed a good modeling of the methane yield and minimized the overfitting effect. For reproduction and solid contribution to the field, we have attached to our article all the necessary material to reproduce the same statistical work as in the paper body.
ISSN:2772-9125
2772-9125
DOI:10.1016/j.clwas.2022.100005