Impact of Carbon-based Nanoparticles on Biogas Yield from Anaerobic Co-Digestion of Cow Dung and Yam Peels

Abstract

The aim of this work is to evaluate the impact of carbon-based nanoparticles on biogas yield from anaerobic co-digestion of cow dung and yam peels. The biomass used for the work include sawdust, cow dung and yam peels. The sawdust was obtained from a saw mill and carbonized in a muffle furnace at 600^oC. It was then ground into fine particles using hammer mill. The Nano-sized sample was chemically activated using 0.85 M phosphoric acid at a 1:1 (by weight) ratio of the sample to the dilute acid. The sample was washed with distilled water until a neutral pH of 7 was obtained. It was then dried in an electric oven at a temperature of 80^oC for 3 hours to obtain the activated carbon-based nanoparticles (ACBNPs). The ACBNPs was characterized using DLS, SEM-EDS, FTIR, XRD and BET. The DLS show that it has a dominant particle size of 11.89 nm confirming that the sample fall within the nanoscale. The SEM results show that the sample has good morphology with contrasts on the surface while the EDS shows that the atomic concentration of carbon in the sample is 71.22, meaning that the carbonization process was successful. The BET results show it has a specific surface area of 250 m²/g and mesoporous particles with good adsorptive properties. The cow dung was collected from a cattle market while the yam peels were collected from a restaurant, pretreated and put in a paste form. The substrates, cow dung and yam peels, were characterized. Microbial assay on the cow dung showed the presence of the microorganisms that are active in anaerobic digestion. Design of experiment (DOE) was generated (a total of 20 runs) using CCD of the design expert software to evaluate the individual and interactive effects of three factors - time, substrate ratio and nanoparticle concentration. Batch experiments were conducted and the daily biogas yields were measured by downward displacement of water in measuring cylinders. Experimental method was employed to evaluate the performance of the anaerobic digestion process while Response Surface Methodology (RSM) was utilized to model the digestion process. The DOE analysis using Response Surface Methodology (RSM) generated a quadratic model showing the individual and interactive effects of the independent factors on the biogas yield. The maximum value of the biogas yield, as predicted by RSM was 2649.5 ml, while the optimal factors were Time (12 days), Substrates mixing ratio (45% or CD: YP ratio of 9:11) and NPs concentration (164 mg/L). The results demonstrated that the addition of nanoparticles significantly improved biogas and methane yields compared to the control (without nanoparticles). Precisely, the biogas yield increased by 33.2% while the methane content increased by 4.1%. This improvement is attributed to enhanced microbial activity, improved electron transfer, and accelerated degradation of complex organic substrates.