Journal article

Publication year: 2021

Journal: Processes

Volume number: 9

Issue number: 5

eISSN: 2227-9717

Open access status: Gold

DOI Link: https://doi.org/10.3390/pr9050877

Publisher: MDPI

Abstract: 
Anaerobic co-digestion (AcoD) is a widely employed technique to produce biogas from simultaneous digestion of various biomasses. However, the selection of the optimal proportions of the substrates in the mixtures presents a challenge. This research used a mixture design to investigate the interactions between the liquid fraction of piglet manure (PM), cow manure (CWM), and starch wastewater (SWW). A modified Gompertz model was used to identify the statistically significant parameters of the methane production curves. The optimal compositions of the mixtures were identified based on multi-objective optimization of the maximal methane yield (Upsilon(CH4)) and maximal methane specific production rate (r(CH4)) parameters. The study was validated using a double mixture of PM and CWM and a triple mixture. The estimated degradation rates for both mixtures were faster than the predicted ones. The absolute relative errors of r(CH4) were 27.41% for the double mixture and 5.59% for the triple mixture, while the relative errors of Y-CH4 were 4.64% for the double mixture and 10.05% for the triple mixture. These relative errors are within the normal limits of a process with high variability like AD. Thus, mixture design supported by the tested models is suitable for the definition of practically advisable mixtures of substrates.

Harvard Citation style: Regalado, R., Weide, T., Baumkoetter, D., Wettwer, L., Haener, J., Bruegging, E., et al. (2021) Optimization and Analysis of Liquid Anaerobic Co-Digestion of Agro-Industrial Wastes via Mixture Design, Processes, 9(5), Article 877. https://doi.org/10.3390/pr9050877

APA Citation style: Regalado, R., Weide, T., Baumkoetter, D., Wettwer, L., Haener, J., Bruegging, E., & Traenckner, J. (2021). Optimization and Analysis of Liquid Anaerobic Co-Digestion of Agro-Industrial Wastes via Mixture Design. Processes. 9(5), Article 877. https://doi.org/10.3390/pr9050877