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Can Biomethane Potential (BMP) Be Predicted from Other Variables Such As Biochemical Composition in Lignocellulosic Biomass and Related Organic Residues?

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Abstract

The potential of methane production by anaerobic digestion of lignocellulosic biomass depends not only on the availability of the resources in the considered territory, but also on their physico-chemical characteristics. Relevant methods of characterization are, therefore, needed to select and possibly combine the most appropriate biomass substrates in order to optimize energy recovery through anaerobic digestion processes. The objective of the present study was to determine whether biomethane potential of such substrates could be predicted from a limited number of variables more rapidly or determined more easily. A set of 36 biomass substrates and organic residues from a variety of origins was analyzed for total and easily hydrosoluble organic matter fractions (volatile solid, VS and soluble chemical oxygen demand, SCOD), neutral detergent soluble fraction (SOL), hemicelluloses (HEM), cellulose (CELL), and lignin-like residual fractions (RES). Bioreactivity of all samples was also measured by experimental assays (biochemical oxygen demand, BOD and biochemical methane potential, BMP). The whole set of data thereby obtained was analyzed statistically considering one dependent variable (BMP), and six independent variables (SCOD, SOL, HEM, CELL, RES, and BOD). Partial least square (PLS) analysis revealed very clearly a positive correlation between BMP and BOD, which were both anti-correlated with RES. On the other hand, no correlations were observed between BMP, SCOD, HEM, and CELL contents. PLS analysis showed that BMP was significantly correlated to the six independent variables. The most influential variables were found to be RES and BOD, and a polynomial model was successfully validated for the prediction of BMP from RES and BOD.

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Abbreviations

AD:

Anaerobic digestion

BD Aero :

Bioconversion yield under aerobic condition

BD Anae :

Bioconversion yield under anaerobic condition

BOD:

Biological oxygen demand after 28 days of incubation as mass of oxygen consumed by TS or VS in 28 days of incubation at 30 °C (g kg−1)

BMP:

Biochemical methane production after 60 days of incubation by VS in 60 days of incubation at 35 °C (L kg−1)

CELL:

Cellulose-like content from Van Soest sequential extraction by VS (g kg−1)

Cellulose:

Cellulose content from NREL extraction procedure by VS (g kg−1)

CODTot :

Total chemical oxygen demand by TS (gO2 kg−1)

HEM:

Hemicellulose-like content from Van Soest sequential extraction by VS (g kg−1)

PLS:

Partial least square analysis

PRESS:

Predicted residual sum of squares

R2 :

Correlation coefficient

RES :

Residual lignin-like content from Van Soest sequential extractions by VS (g kg−1)

RMSW:

Residual municipal solid waste

rRMSE:

Relative root mean square error

SCOD:

Soluble chemical oxygen demand by VS in leachate collected from leaching test at a L/S ratio of 10 (gO2 kg−1)

SOL:

Soluble fraction from Van Soest sequential extractions by VS (g kg−1)

TOC:

Total organic carbon by TS (g kg−1)

TS:

Total solid

VIP:

Variable importance in projection

VS:

Volatile solid (g kg−1)

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Authors and Affiliations

  1. Université de Lyon, INSA Lyon, LGCIE-DEEP, EA4126, 69621, Villeurbanne cedex, France

    Rémy Bayard, Xun Liu, Hassen Benbelkacem, Pierre Buffiere & Rémy Gourdon

Authors
  1. Rémy Bayard
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  2. Xun Liu
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  3. Hassen Benbelkacem
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  4. Pierre Buffiere
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  5. Rémy Gourdon
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Correspondence to Rémy Bayard.

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Highlights

• Biomethane potential (BMP) and biological oxygen demand (BOD) were both anti-correlated with Van Soest’s residual fraction (RES).

• For substrates representative of the large ranges of biochemical compositions, no clear correlations were observed between BMP, soluble COD (SCOD), hemicellulose (HEM), and (CELL) contents.

• The most influential variables to predict BMP were found to be RES and BOD.

• A polynomial model was successfully validated for the prediction of BMP from RES and BOD.

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Bayard, R., Liu, X., Benbelkacem, H. et al. Can Biomethane Potential (BMP) Be Predicted from Other Variables Such As Biochemical Composition in Lignocellulosic Biomass and Related Organic Residues?. Bioenerg. Res. 9, 610–623 (2016). https://doi.org/10.1007/s12155-015-9701-3

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  • DOI: https://doi.org/10.1007/s12155-015-9701-3

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