Modelling anaerobic digestion in an industrial biogas digester: Application of lactate-including ADM1 model (Part II).

A modified Anaerobic Digestion Model No. 1 (ADM1xp) including lactate was applied to a full-scale biogas plant. This model considers monosaccharides to degrade through lactic acid, which further degrades majorly into acetate followed by propionate and butyrate. Experimental data were derived from the previous works in the same laboratory, and the proposed parameters were validated against batch experiments. After successful validation, the biogas plant bearing a fermenter size of 7 dam3 and operated with food waste and cattle manure was simulated. The biogas production and methane content were reliably simulated, and a good fit could be obtained against the experimental data with an average difference of less than 1%. When compared to the original ADM1 model, the performance of the lactate-incorporated model was found to be improved. Inclusion of lactate as a parameter in the ADM1xp model is recommended for an increased sensitivity and enhanced prediction principally for systems dealing with high carbohydrate and lactate loads.

Modelling anaerobic digestion in a biogas reactor: ADM1 model development with lactate as an intermediate (Part I).

The Anaerobic Digestion Model No. 1 (ADM1) was extended to include lactate, a crucial metabolic product during sugar fermentation. This study tests the validity of the modified ADM1 model in improving the predictions of a standard biogas reactor. This reactor was prepared in the laboratory with simple organic substrates with an intention to represent an 'average biogas plant'. Kinetic parameters were determined from a lactic acid enriched steady-state reactor. The parameters were adjusted further in order to acquire satisfying simulation results systematically with the batch experiments and then against the standard biogas reactor. Arresting methanogenesis revealed that lactate degradation occurred majorly via acetate followed by propionate, and a non-negligible proportion of butyrate too was found, which were further updated in the model. The modified ADM1 provided a successful correlation with the experimental results for the batch and continuous experiments. We justified that inclusion of lactate in the model resulted in optimized simulation for both biogas and methane content in the standard biogas reactor.

Different substrates and starter inocula govern microbial community structures in biogas reactors.

The influence of different starter inocula on the microbial communities in biogas batch reactors fed with fresh maize and maize silage as substrates was investigated. Molecular biological analysis by Denaturing Gradient Gel Electrophoresis (DGGE) of 16S rRNA gene fragments showed that each inoculum bore specific microbial communities with varying predominant phylotypes. Both, bacterial and archaeal DGGE profiles displayed three distinct communities that developed depending on the type of inoculum. Although maize and silage are similar substrates, different communities dominated the lactate-rich silage compared to lactate-free fresh maize. Cluster analysis of DGGE gels showed the communities of the same substrates to be stable with their respective inoculum. Bacteria-specific DGGE analysis revealed a rich diversity with Firmicutes being predominant. The other abundant phylotypes were Bacteroidetes and Synergistetes. Archaea-specific DGGE analysis displayed less diverse community structures, identifying members of the Methanosarcinales as the dominant methanogens present in all the three biogas digesters. In general, the source of inoculum played a significant role in shaping microbial communities. Adaptability of the inoculum to the substrates fed also influenced community compositions which further impacted the rates of biogas production.