Please cite this article as: J.P. Díaz, I.P. Reyes, M.J. Taherzadeh, I.S. Horváth, M. Lundin, Anaerobic co-digestion of solid slaughterhouse wastes with agro-residues: Synergistic and antagonistic interactions determined in batch digestion assays, Chemical Engineering Journal (2014), doi: http://dx.doi.org/10. 1016/j.cej.2014.02.008 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
AbstractDifferent mixture ratios of solid cattle slaughterhouse wastes (SB), manure (M), various crops (VC), and municipal solid wastes (MSW) were investigated for biogas production. The objective was to explore possible significant synergistic effects obtained from the combination of these different substrates. The performance of the process was assessed in thermophilic anaerobic batch co-digestion assays, using a four factor mixture design and methane yield (Y CH4 ) and specific methane production rate (r sCH4 ) as response variables.The highest methane yield, 655 NmL CH 4 /g VS was obtained when equal parts (ww) of SB, M, VC, and MSW were combined, while the combination of SB, M, and MSW resulted in the highest specific methane production rate (43 NmL CH 4 /g VS/d). A mixture design model was fitted to data in order to appraise synergistic and antagonistic interactions. Mixing all four substrates resulted in a 31% increase of the expected yield which was calculated from the methane potential of the individual fractions, clearly demonstrating a synergistic effect due to more balanced nutrient composition enhancing the anaerobic digestion process. However, no significant antagonistic effects were observed. In order to maximize both response variables simultaneously, a response surface method was employed to establish the optimal combination of substrate mixtures. The statistical results and analysis of the biological process gave a coherent picture of the results.