Composition-oriented estimation of biogas production from major culinary wastes in an anaerobic bioreactor and its associated CO2 reduction potential
[Display omitted] •The effect of various operating factors on the biogas production was explored.•Response surface models were developed to predict biogas production and kinetics.•Microbial communities were analyzed to understand the behaviors and mechanisms.•The potential of net CO2 reduction by AD...
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Veröffentlicht in: | Bioresource technology 2020-12, Vol.318, p.124045-124045, Article 124045 |
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Format: | Artikel |
Sprache: | eng |
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•The effect of various operating factors on the biogas production was explored.•Response surface models were developed to predict biogas production and kinetics.•Microbial communities were analyzed to understand the behaviors and mechanisms.•The potential of net CO2 reduction by AD was estimated using life cycle assessment.•A substantial amount of CO2 (2.8–6.7 ton per ton-VS) could be avoided by AD.
Despite the wide applications of dry anaerobic digestion (AD), a number of fundamental issues, such as composition-oriented estimation of biogas production and CO2 reduction potential, were not well understood yet. The objective of this study was to establish composition-oriented models for prediction of biogas production and the associated shift of microbial communities. Three important factors regarding feedstock, including loading, carbon-to-nitrogen ratio, and solid-to-liquid ratio, were found to significantly affect the biogas production. The biogas production and digestion kinetics were evaluated with the response surface methodology. The major contribution to biogas production was found to be hydrogenotrophic methanogens (82.6 ± 0.4%). The net CO2 reduction potential was assessed from the life-cycle approach, and a substantial amount of CO2 generation (i.e., 2.8–6.7 tonne/tonne-VS) could be reduced by AD, compared to incineration, revealing that dry AD for food waste treatment should be one of the essential practices in the portfolio of global CO2 mitigation. |
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ISSN: | 0960-8524 1873-2976 |
DOI: | 10.1016/j.biortech.2020.124045 |