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Addressing case specific biogas plant tasks: Industry oriented methane yields derived from 5L Automatic Methane Potential Test Systems in batch or semi-continuous tests using realistic inocula, substrate particle sizes and organic loading
•In-house upscale of Automatic Methane Potential Test System to 5L was developed.•Full-scale inocula, substrates and organic loading were used in tests.•Tests were characterized by short preparation times, accuracy and high-through put.•Same scales, equipment and methodologies were used in batch and...
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Published in: | Bioresource technology 2014-02, Vol.153, p.180-188 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •In-house upscale of Automatic Methane Potential Test System to 5L was developed.•Full-scale inocula, substrates and organic loading were used in tests.•Tests were characterized by short preparation times, accuracy and high-through put.•Same scales, equipment and methodologies were used in batch and continuous tests.•Increased full-scale decision making value of the developed approach was shown.
The primary aim of the study was to develop and validate an in-house upscale of Automatic Methane Potential Test System II for studying real-time inocula and real-scale substrates in batch, codigestion and enzyme enhanced hydrolysis experiments, in addition to semi-continuous operation of the developed equipment and experiments testing inoculum functional quality. The successful upscale to 5L enabled comparison of different process configurations in shorter preparation times with acceptable accuracy and high-through put intended for industrial decision making. The adoption of the same scales, equipment and methodologies in batch and semi-continuous tests mirroring those at full scale biogas plants resulted in matching methane yields between the two laboratory tests and full-scale, confirming thus the increased decision making value of the approach for industrial operations. |
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ISSN: | 0960-8524 1873-2976 |
DOI: | 10.1016/j.biortech.2013.12.010 |