Benchmarking real-time monitoring strategies for ethanol production from lignocellulosic biomass

被引:26
作者
Lopez, Pau Cabaneros [1 ]
Feldman, Hannah [1 ]
Mauricio-Iglesias, Miguel [2 ]
Junicke, Helena [1 ]
Huusom, Jakob Kjobsted [1 ]
Gernaey, Krist, V [1 ]
机构
[1] Tech Univ Denmark DTU, PROSYS Res Ctr, Dept Chem & Biochem Engn, Bldg 229, DK-2800 Lyngby, Denmark
[2] Univ Santiago de Compostela, Dept Chem Engn, Santiago De Compostela 15782, Spain
关键词
Real-time monitoring; Monitoring devices; Fermentation; Models; Soft sensors; Cellulosic ethanol; NEAR-INFRARED SPECTROSCOPY; 2-DIMENSIONAL FLUORESCENCE SPECTROSCOPY; PARALLEL FACTOR-ANALYSIS; SACCHAROMYCES-CEREVISIAE; FLOW-CYTOMETRY; SIMULTANEOUS SACCHARIFICATION; ALCOHOLIC FERMENTATION; MULTIWAVELENGTH FLUORESCENCE; YEAST FERMENTATION; RAMAN-SPECTROSCOPY;
D O I
10.1016/j.biombioe.2019.105296
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
The goal of this paper is to review and critically assess different methods to monitor key process variables for ethanol production from lignocellulosic biomass. Because cellulose-based biofuels cannot yet compete with non-cellulosic biofuels, process control and optimization are of importance to lower the production costs. This study reviews different monitoring schemes, to indicate what the added value of real-time monitoring is for process control. Furthermore, a comparison is made on different monitoring techniques to measure the off-gas, the concentrations of dissolved components in the inlet to the process, the concentrations of dissolved components in the reactor, and the biomass concentration. Finally, soft sensor techniques and available models are discussed, to give an overview of modeling techniques that analyze data, with the aim of coupling the soft sensor predictions to the control and optimization of cellulose to ethanol fermentation. The paper ends with a discussion of future needs and developments.
引用
收藏
页数:14
相关论文
共 111 条
  • [1] Automated flow cytometry for acquisition of time-dependent population data
    Abu-Absi, NR
    Zamamiri, A
    Kacmar, J
    Balogh, SJ
    Srienc, F
    [J]. CYTOMETRY PART A, 2003, 51A (02): : 87 - 96
  • [2] On-line parallel factor analysis. A step forward in the monitoring of bioprocesses in real time
    Amigo, Jose Manuel
    Surribas, Anna
    Coello, Jordi
    Montesinos, Jose Luis
    Maspoch, Santiago
    Valero, Francisco
    [J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2008, 92 (01) : 44 - 52
  • [3] [Anonymous], UPSTREAM IND BIOTECH
  • [4] Athmanathan A., 2010, Biological Engineering, V3, P111, DOI 10.13031/2013.36315
  • [5] Austin G., 2015, WO 2015/095255 A1, Patent No. 2015095255
  • [6] STUDIES OF ONLINE VIABLE YEAST BIOMASS WITH A CAPACITANCE BIOMASS MONITOR
    AUSTIN, GD
    WATSON, RWJ
    DAMORE, T
    [J]. BIOTECHNOLOGY AND BIOENGINEERING, 1994, 43 (04) : 337 - 341
  • [7] Phenotypic variability in bioprocessing conditions can be tracked on the basis of on-line flow cytometry and fits to a scaling law
    Baert, Jonathan
    Kinet, Romain
    Brognaux, Alison
    Delepierre, Anissa
    Telek, Samuel
    Sorensen, Soren J.
    Riber, Leise
    Fickers, Patrick
    Delvigne, Frank
    [J]. BIOTECHNOLOGY JOURNAL, 2015, 10 (08) : 1316 - 1325
  • [8] Microfiltration of activated sludge wastewater - the effect of system operation parameters
    Bai, RB
    Leow, HF
    [J]. SEPARATION AND PURIFICATION TECHNOLOGY, 2002, 29 (02) : 189 - 198
  • [9] YEAST FERMENTATION OF SUGARCANE FOR ETHANOL PRODUCTION: CAN IT BE MONITORED BY USING IN SITU MICROSCOPY?
    Belini, V. L.
    Caurin, G. A. P.
    Wiedemann, P.
    Suhr, H.
    [J]. BRAZILIAN JOURNAL OF CHEMICAL ENGINEERING, 2017, 34 (04) : 949 - 959
  • [10] In situ microscopy: A perspective for industrial bioethanol production monitoring
    Belini, Valdinei Luis
    Wiedemann, Philipp
    Suhr, Hajo
    [J]. JOURNAL OF MICROBIOLOGICAL METHODS, 2013, 93 (03) : 224 - 232