A review of dark fermentative hydrogen production from biodegradable municipal waste fractions

Highlights: ► A large number of factors affect fermentative hydrogen production. ► Harmonization and systematic comparison of results from different literature sources are needed. ► More than 80 publications on H2 production from food waste and OFMSW have been examined. ► Experimental data from the reviewed literature were analyzed using statistical tools. ► For a reliable assessment of the process performance, the use of multiple parameters appears to be recommended. - Abstract: Hydrogen is believed to play a potentially key role in the implementation of sustainable energy production, particularly when it is produced from renewable sources and low energy-demanding processes. In the present paper an attempt was made at critically reviewing more than 80 recent publications, in order to harmonize and compare the available results from different studies on hydrogen production from FW and OFMSW through dark fermentation, and derive reliable information about process yield and stability in view of building related predictive models. The review was focused on the effect of factors, recognized as potentially affecting process evolution (including type of substrate and co-substrate and relative ratio, type of inoculum, food/microorganisms [F/M] ratio, applied pre-treatment, reactor configuration, temperature and pH), on the fermentation yield and kinetics. Statistical analysis of literature data from batch experiments was also conducted, showing that the variables affecting the H2 production yield were ranked in the order: type of co-substrate, type of pre-treatment, operating pH, control of initial pH and fermentation temperature. However, due to the dispersion of data observed in some instances, the ambiguity about the presence of additional hidden variables cannot be resolved. The results from the analysis thus suggest that, for reliable predictive models of fermentative hydrogen production to be derived, a high level of consistency between data is strictly required, claiming for more systematic and comprehensive studies on the subject