Early prediction of Biochemical Methane Potential through statistical and kinetic modelling of initial gas production

被引：62
作者：
Stromberg, Sten [1 ]
Nistor, Mihaela [2 ]
Liu, Jing [1 ,2 ]
机构：
[1] Lund Univ, Dept Biotechnol, S-22100 Lund, Sweden
[2] Bioproc Control AB, S-22363 Lund, Sweden
来源：
BIORESOURCE TECHNOLOGY | 2015年 / 176卷
关键词：
Anaerobic digestion; Biochemical Methane Potential; Biogas; Kinetic model; Predicting BMP; INFRARED REFLECTANCE SPECTROSCOPY; ANAEROBIC-DIGESTION; RAPID-DETERMINATION; SOLID-WASTES; BIOGAS; BIOMASS; BIODEGRADABILITY; YIELDS; BMP;
D O I：
10.1016/j.biortech.2014.11.033
中图分类号：
S2 [农业工程];
学科分类号：
0828 ;
摘要：
A major drawback of Biochemical Methane Potential (BMP) tests is their long test duration, which could be reduced substantially if the final gas production could be predicted at an earlier stage. For this purpose, this study evaluates 61 different algorithms for their capability to predict the final BMP and required degradation time based on data from 138 BMP tests of various substrate types. By combining the best algorithms it was possible to predict the BMP with a relative root mean squared error (rRMSE) of less than 10% just 6 days after initiation of the experiment. The results from this study indicate that there is a possibility to shorten the test length substantially by combining laboratory tests and intelligent prediction algorithms. Shorter test duration may widen the possible applications for BMP tests in full-scale biogas plants, allowing for a better selection and proper pricing of biomass. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码：233 / 241
页数：9
相关论文
共 28 条
[21]   Predicting anaerobic biogasification potential of ingestates and digestates of a full-scale biogas plant using chemical and biological parameters [J].
Schievano, Andrea ;
Pognani, Michele ;
D'Imporzano, Giuliana ;
Adani, Fabrizio .
BIORESOURCE TECHNOLOGY, 2008, 99 (17) :8112-8117
[22]   Prediction of biogas potentials using quick laboratory analyses: Upgrading previous models for application to heterogeneous organic matrices [J].
Schievano, Andrea ;
Scaglia, Barbara ;
D'Imporzano, Giuliana ;
Malagutti, Luca ;
Gozzi, Annalisa ;
Adani, Fabrizio .
BIORESOURCE TECHNOLOGY, 2009, 100 (23) :5777-5782
[23]   Anaerobic digestion of organic fraction of municipal solid waste combining two pretreatment modalities, high temperature microwave and hydrogen peroxide [J].
Shahriari, Haleh ;
Warith, Mostafa ;
Hamoda, Mohamed ;
Kennedy, Kevin J. .
WASTE MANAGEMENT, 2012, 32 (01) :41-52
[24]   Towards eliminating systematic errors caused by the experimental conditions in Biochemical Methane Potential (BMP) tests [J].
Stroemberg, Sten ;
Nistor, Mihaela ;
Liu, Jing .
WASTE MANAGEMENT, 2014, 34 (11) :1939-1948
[25]  
Stromberg S., 2014, IWA WORLD WAT C EXH
[26]   Statistical prediction of biomethane potentials based on the composition of lignocellulosic biomass [J].
Thomsen, Sune Tjalfe ;
Spliid, Henrik ;
Ostergard, Hanne .
BIORESOURCE TECHNOLOGY, 2014, 154 :80-86
[27]   Near Infrared Reflectance Spectroscopy (NIRS) for rapid determination of biochemical methane potential of plant biomass [J].
Triolo, Jin M. ;
Ward, Alastair J. ;
Pedersen, Lene ;
Lokke, Mette M. ;
Qu, Haiyan ;
Sommer, Sven G. .
APPLIED ENERGY, 2014, 116 :52-57
[28]   A new algorithm to characterize biodegradability of biomass during anaerobic digestion: Influence of lignin concentration on methane production potential [J].
Triolo, Jin M. ;
Sommer, Sven G. ;
Moller, Henrik B. ;
Weisbjerg, Martin R. ;
Jiang, Xin Y. .
BIORESOURCE TECHNOLOGY, 2011, 102 (20) :9395-9402
123