Direct inoculation of a biotrickling filter for hydrogenotrophic methanogenesis.

Hydrogenotrophic biomethanation in a biotrickling filter has been reported to be a proven technology for biological biogas upgrading in recent studies. However, the preparation of enriched hydrogenotrophic methanogens in a separate reactor prior to biomethanation in a trickled bed is a lengthy procedure and therefore hard to apply on an industrial scale. This study explored the direct inoculation of anaerobic biogas digestate for simultaneous enrichment of hydrogenotrophic methanogens and biofilm immobilisation in a trickled bed system. The direct inoculation and formation of hydrogenotrophic biofilm was successful and resulted in a stable H2 loading rate of 11  [Formula: see text] , with the highest specific methane productivity recorded at 3.03 Nm3mR-3d-1 and a purity of 98% CH4 in thermophilic conditions. The DNA analysis confirmed that hydrogenotrophic methanogens dominated the archaeal consortia.

Influence of chemical composition on biochemical methane potential of fruit and vegetable waste.

This study investigates the influence of chemical composition on the biochemical methane potential (BMP) of twelve different batches of fruit and vegetable waste (FVW) with different compositions collected over one year. BMP ranged from 288 to 516LNCH4kgVS-1, with significant statistical differences between means, which was explained by variations in the chemical composition over time. BMP was most strongly correlated to lipid content and high calorific values. Multiple linear regression was performed to develop statistical models to more rapidly predict methane potential. Models were analysed that considered chemical compounds and that considered only high calorific value as a single parameter. The best BMP prediction was obtained using the statistical model that included lipid, protein, cellulose, lignin, and high calorific value (HCV), with R2 of 92.5%; lignin was negatively correlated to methane production. Because HCV and lipids are strongly correlated, and because HCV can be determined more rapidly than overall chemical composition, HCV may be useful for predicting BMP.