| Literature DB >> 27888663 |
Jorge Gonzalez-Estrella1, Caitlin M Asato1, Amber C Jerke1, James J Stone2, Patrick C Gilcrease1.
Abstract
Anaerobic digestion (AD) of lignocellulosic materials is commonly limited by the hydrolysis step. Unlike unprocessed lignocellulosic materials, paper and paper board (PPB) are processed for their fabrication. Such modifications may affect their methane yields and methane production rates. Previous studies have investigated the correlation between lignin and biomethane yields of unprocessed lignocellulosic materials; nevertheless, there is limited knowledge regarding the relationship between the AD kinetic parameters and composition of PPB. This study evaluated correlations of methane yields and Monod and Gompertz kinetic parameters with structural carbohydrates, lignin, and ash concentration of five types of PPBs. All components were used as single and combined independent variables in linear regressions to predict methane yield, maximum specific methanogenic activity (SMAmax ), saturation constant (Ks ), and lag phase (λ). Additionally, microbial community profiles were obtained for each PPB assay. Results showed methane yields ranging from 69.2 ± 8.61 to 97.2 ± 2.29% of PPB substrates provided. The highest correlation coefficients were obtained for SMAmax as function of hemicellulose/(lignin + ash) (R2 = 0.86) and for λ as a function of lignin + cellulose (R2 = 0.85). All other parameters exhibited weaker correlations (R2 ≤ 0.77). Relative abundance analyses revealed no major changes in the community profile for each of the substrates evaluated. The overall findings of this study are: (i) combinations of structural carbohydrates, lignin, and ash used as ratios of degradable to either non-degradable or slowly degradable fractions predict AD kinetic parameters of PPB materials better than single independent variables; and (ii) other components added during their fabrication may also influence both methane yield and kinetic parameters. Biotechnol. Bioeng. 2017;114: 951-960.Entities:
Keywords: biomethane potential; lignocellulose; linear regression; methanogenesis; predicting parameters; solid waste
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Year: 2016 PMID: 27888663 DOI: 10.1002/bit.26228
Source DB: PubMed Journal: Biotechnol Bioeng ISSN: 0006-3592 Impact factor: 4.530