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Optimization of biogas productivity in lab-scale by response surface methodology

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  • Safari, Mahmood
  • Abdi, Reza
  • Adl, Mehrdad
  • Kafashan, Jalal

Abstract

Optimization of canola residues in co-digestion with cattle manure for enhanced biogas yield was carried out using response surface methodology (RSM) and Box – Behnken design of the experiment. The effects of inoculum, total solids (TS), temperature (psychrophilic, mesophilic and thermophilic conditions) and stirring time (duration) in three levels were investigated. After applying of thermo mechanical pretreatment, 29 tests were performed. The experimental results showed that the temperature variable had the greatest effect in the model. The optimum degree of variables achieved in anaerobic digestion was 52.49 °C of temperature, 3.12 min day−1 of stirring time, 7.02% TS of substrate working volume and 22.17% inoculum (22.17% TS) with a methane yield of 403.63 L kg−1 in thermophilic conditions. The optimum degree of variables was: stirring time 3.57 min day−1, 7.41% TS of substrate working volume, 26.26% inoculum (26.26% TS) and temperature at 40.36 °C with a methane yield of 376.76 L kg−1VS in mesophilic conditions. The high value of R2 (0.9983) showed that the model can efficiently be applied to prediction of methane production from the co-digestion of cattle manure and canola residues. Both mesophilic and thermophilic conditions were suitable in terms of energy production, however, the mesophilic conditions showed more positive energy balance and higher Net Energy Gain (NEG) than the thermophilic conditions.

Suggested Citation

  • Safari, Mahmood & Abdi, Reza & Adl, Mehrdad & Kafashan, Jalal, 2018. "Optimization of biogas productivity in lab-scale by response surface methodology," Renewable Energy, Elsevier, vol. 118(C), pages 368-375.
    • Handle: RePEc:eee:renene:v:118:y:2018:i:c:p:368-375
    DOI: 10.1016/j.renene.2017.11.025
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    3. Noonari, Altaf Alam & Mahar, Rasool Bux & Sahito, Abdul Razaque & Brohi, Khan Muhammad, 2020. "Effects of isolated fungal pretreatment on bio-methane production through the co-digestion of rice straw and buffalo dung," Energy, Elsevier, vol. 206(C).
    4. Olatunji, Kehinde O. & Ahmed, Noor A. & Madyira, Daniel M. & Adebayo, Ademola O. & Ogunkunle, Oyetola & Adeleke, Oluwatobi, 2022. "Performance evaluation of ANFIS and RSM modeling in predicting biogas and methane yields from Arachis hypogea shells pretreated with size reduction," Renewable Energy, Elsevier, vol. 189(C), pages 288-303.
    5. Zhan, Yuanhang & Zhu, Jun & Schrader, Leland C. & Wang, Dongyi, 2023. "Modeling and optimization of bioenergy production from co-digestion of poultry litter with wheat straw in anaerobic sequencing batch reactor: Response surface methodology and artificial neural network," Applied Energy, Elsevier, vol. 345(C).

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