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Title:

Prediction Parameter for Bio-Methanation Production Potential of Lignocellulosic Feedstocks

Author(s):

Paliwal, A., Chanakya, H.N., Dasappa, S., Sinha, I., Somavarapu, S., Pnavale, S.

Document(s):

Paper Paper

Poster Poster

Abstract:

Lignocellulosic residues have a resource base of 200 BT. However, the resource base is spread and wide diversity exists in lignocellulose (~12,570 angiosperms and gymnosperms). The diversity of the lignocellulose confers significant variation in degradation behaviour and gas production during anaerobic digestion (AD). Behaviour generalization and reactor designing for AD of lignocellulose fed reactors are therefore difficult. Utilization of the lignocellulose resource pool for biogas production mandates a parameter/criterion for fast selection of feedstock for use in AD and an estimate of achievable methane yield. A general prediction parameter for use with both monocots and dicots is, therefore, necessary. This study attempted to formulate a potential prediction parameter for the bio-methanation potential (BMP) using 9 lignocellulosic species (5 dicots and 4 agro residues). The study proposes, that the lag phase in methane (LPM), and biogas (LPB), and a dimensionless parameter formulated from the composition ‘(......+......+..+....)’, can be used to predict the methane yield (HWE= hot water extractives, Ox – oxalate extractives, HC=hemicellulose, C=cellulose, L=lignin). The study concluded that lignocellulosics which confers ............ ratio of <2, (......+......+..+....) ratio of >1.16, corroborated to methane yield greater than 338 l/kg VS, and are hence likely to be better feedstocks for bio-methane production.

Keywords:

anaerobic digestion, lignocellulose composition, lignocellulosic feedstock, BMP, BMP prediction, lag phase

Topic:

Biomass Conversion for Bioenergy

Subtopic:

Anaerobic digestion for biogas and biomethane production

Event:

30th European Biomass Conference and Exhibition

Session:

4CV.10.7

Pages:

823 - 831

ISBN:

978-88-89407-22-6

Paper DOI:

10.5071/30thEUBCE2022-4CV.10.7

Price:

FREE