Optimization of Biogas Yield From Anaerobic Co-Digestion of Corn-Chaff and Cow Dung Digestate: RSM and Python Approach

Abstract

Utilization of various feedstocks of unique characteristics in producing biogas could potentially enhance the application of clean fuel from biomass wastes. This study modeled biogas production from corn chaff inoculated with Cow dung digestate via anaerobic fermentation process using Response surface methodology and python coding. Different concentration ratios of Substrate/Inoculum (S/I) of 1:1, 1: 1.55, 1:3.5 were used to digest corn chaff for 25, 31 and 37 days Hydraulic Retention Time (HRT). The mixing ratio of S/I and HRT of the anaerobic digestion was modeled using Central Composite Design (Face Centered Design) and the process response, cumulative biogas yield was optimized. The result shows that the mixing ratio of 0.65 (1:1.55) and HRT of 37 days gave the optimum yield under mesophilic conditions with corresponding biogas production of 6.19L. The model developed is significant and both CCD and python coding are reliable in the optimization of biogas production as they both predicted same biogas yield. Characterization of produced biogas revealed that it contains 68% methane and 22.76% CO2, other constituents present are corroborated by FTIR spectroscopy result. The methane in produced biogas has a flash point of -182 oC. This shows that both CCD and python coding can model biogas production with high accuracy and biogas produced can be used for heating purposes.