Experimental Assessment of Mesophilic and Thermophilic Batch Fermentative Biohydrogen Production from Palm Oil Mill Effluent Using Response Surface Methodology

- The present work evaluated the production of biohydrogen under mesophilic and thermophilic conditions through dark fermentation of palm oil mill effluent (POME) in batch mode using the design of experiment methodology. Response surface methodology (RSM) was applied to investigate the influence of the two significant parameters, POME concentration as substrate (5, 12.5, and 20 g/l), and volumetric substrate to inoculum ratio (1:1, 1:1.5, and 1:2, v/v.%), with inoculum concentration of 14.3 g VSS/l. All the experiments were analyzed at 37 celcius and 55 celcius at an incubation time of 24 h. The highest chemical oxygen demand (COD) removal, hydrogen content (H2%), and hydrogen yield (HY) at a substrate concentration of 12.5 g COD/l and S:I ratio of 1:1.5 in mesophilic and thermophilic conditions were obtained (27.3, 24.2%), (57.92, 66.24%), and (6.43, 12.27 ml H2/g CODrem), respectively. The results show that thermophilic temperature in terms of COD removal was more effective for higher COD concentrations than for lower concentrations. Optimum parameters projected by RSM with S:I ratio of 1:1.6 and POME concentration of 14.3 g COD/l showed higher results in both temperatures. It is recognized how RSM and optimization processes can predict and affect the process performance under different operational conditions.

Automated summary

This study evaluated the production of biohydrogen from palm oil mill effluent (POME) through dark fermentation under mesophilic and thermophilic conditions. Response surface methodology (RSM) was used to investigate the influence of POME concentration and volumetric substrate to inoculum ratio on the process performance. The results showed that the highest COD removal, hydrogen content, and hydrogen yield were obtained at a substrate concentration of 12.5 g COD/l and S:I ratio of 1:1.5 in both temperatures. The optimized parameters projected by RSM showed better results in terms of process performance.