Optimization and modelling of volatile fatty acid generation in a leachate bed reactor for utilization in microbial fuel cells

Volatile fatty acid (VFA)-rich leachate generated from acidogenesis of kitchen waste in a leach bed reactor (LBR) was utilized in an earthen microbial fuel cell (EMFC) to generate electricity. Effects of organic loading rate (OLR, 5-10 g VS/L center dot day) and pH (5-7) on LBR enumerated optimized parameters of OLR (10 g VS/L center dot day) and pH (5.74) to obtain total VFA (TVFA) of 7.7 +/- 0.3 g/L in the leachate, with maximum contribution from acetic acid. Leachate obtained from the LBR was fed to the EMFC with varying OLR (2-7 kg COD/m(3)center dot day). The highest power density of 0.76 W/m(3) (at OLR 7 kg COD/m(3)center dot day) was obtained with higher VFA content in the leachate. A neural network based on the Levenberg-Marquard function effectively predicted chemical oxygen demand and TVFA removal. This study establishes LBR as a techno-economic method to obtain useful substrate for EMFC. Furthermore, the response modelling of EMFC demonstrates the potential of utilizing machine learning in biological treatment.