Advances in Modeling Anaerobic Digestion

A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Microbial Biotechnology".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 7776

Special Issue Editors

Department of Environmental Microbiology, Helmholtz Centre for Environmental Research—UFZ, 04318 Leipzig, Germany
Interests: systems biology; mathematical modeling; microbiomes; anaerobic digestion; microbial ecology; microbial biotechnology; bioinformatics
Department of Environmental Microbiology, Helmholtz Centre for Environmental Research—UFZ, Leipzig, Germany
Interests: anaerobic digestion; anaerobic fermentation; microbial ecology; modeling of microbial communities; multi-omics
Biochemical Conversion Department, Deutsches Biomasseforschungszentrum gemeinnützige GmbH, Leipzig, Germany
Interests: anaerobic digestion; biogas technology; model development and validation; process monitoring and control; assessment and enhancement of laboratory methods

Special Issue Information

Dear Colleagues,

Anaerobic digestion is a naturally occurring multi-step process in which organic material is ultimately transformed to methane by a complex microbial community. While also occurring in natural habitats, this process is most prominently harnessed in biogas plants, providing a source of renewable energy and utilizing waste streams. Process-based mathematical modeling of anerobic digestion has a long tradition. It has been crucial in uncovering the intricate biotic and abiotic interactions and dependencies driving the process, and has been indispensable for optimizing reactor performance. Suitable models are also reliable tools for plant design or the development of new processes and applications such as in-situ methanization (Power2Gas), the carboxylate platform, or flexible on-demand reactor operation.

This Special Issue will focus on recent developments and applications in anaerobic process modeling. Contributions providing novel theoretical insights into process dynamics, as well as studies incorporating experimental data (from lab- to industry-scale), are invited. In both cases, the implications of reported findings or modeling concepts for future anaerobic digestion applications should be stated.

We are particularly interested in contributions related to the following topics:

  • Model development, including
    -Enhancement of existing models;
    -Thermodynamic modeling;
    -Microbial species-resolved approaches;
    -OMICS data integration;
    -Novel AD processes and applications.
  • Model application and validation;
  • Parameter estimation and system identification;
  • Model-based process monitoring and control;
  • Novel modeling concepts (e.g., AI applications).

We are looking forward to your contribution! Please contact us with any questions.

 

Dr. Florian Centler
Dr. Denny Popp
Dr. Sören Weinrich
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Microorganisms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • anaerobic digestion
  • biogas technology
  • model development
  • parameter estimation
  • process control
  • process optimization
  • quantitative modeling

Published Papers (3 papers)

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Research

14 pages, 2445 KiB  
Article
Comprehensive ADM1 Extensions to Tackle Some Operational and Metabolic Aspects in Anaerobic Digestion
by Andrés Donoso-Bravo, María Constanza Sadino-Riquelme, Emky Valdebenito-Rolack, David Paulet, Daniel Gómez and Felipe Hansen
Microorganisms 2022, 10(5), 948; https://doi.org/10.3390/microorganisms10050948 - 30 Apr 2022
Cited by 3 | Viewed by 1859
Abstract
Modelling in anaerobic digestion will play a crucial role as a tool for smart monitoring and supervision of the process performance and stability. By far, the Anaerobic Digestion Model No. 1 (ADM1) has been the most recognized and exploited model to represent this [...] Read more.
Modelling in anaerobic digestion will play a crucial role as a tool for smart monitoring and supervision of the process performance and stability. By far, the Anaerobic Digestion Model No. 1 (ADM1) has been the most recognized and exploited model to represent this process. This study aims to propose simple extensions for the ADM1 model to tackle some overlooked operational and metabolic aspects. Extensions for the discontinuous feeding process, the reduction of the active working volume, the transport of the soluble compound from the bulk to the cell interior, and biomass acclimation are presented in this study. The model extensions are included by a change in the mass balance of the process in batch and continuous operation, the incorporation of a transfer equation governed by the gradient between the extra- and intra- cellular concentration, and a saturation-type function where the time has an explicit influence on the kinetic parameters, respectively. By adding minimal complexity to the existing ADM1, the incorporation of these phenomena may help to understand some underlying process issues that remain unexplained by the current model structure, broadening the scope of the model for control and monitoring industrial applications. Full article
(This article belongs to the Special Issue Advances in Modeling Anaerobic Digestion)
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14 pages, 1324 KiB  
Article
Model Predictive Control: Demand-Orientated, Load-Flexible, Full-Scale Biogas Production
by Celina Dittmer, Benjamin Ohnmacht, Johannes Krümpel and Andreas Lemmer
Microorganisms 2022, 10(4), 804; https://doi.org/10.3390/microorganisms10040804 - 12 Apr 2022
Cited by 2 | Viewed by 1741
Abstract
Biogas plants have the great advantage that they produce electricity according to demand and can thus compensate for fluctuating production from weather-dependent sources such as wind power and photovoltaics. A prerequisite for flexible biogas plant operation is a suitable feeding strategy for an [...] Read more.
Biogas plants have the great advantage that they produce electricity according to demand and can thus compensate for fluctuating production from weather-dependent sources such as wind power and photovoltaics. A prerequisite for flexible biogas plant operation is a suitable feeding strategy for an adjusted conversion of biomass into biogas. This research work is the first to demonstrate a practical, integrated model predictive control (MPC) for load-flexible, demand-orientated biogas production and the results show promising options for practical application on almost all full-scale biogas plants with no or only minor adjustments to the standardly existing measurement technology. Over an experimental period of 36 days, the biogas production of a full-scale plant was adjusted to the predicted electricity demand of a “real-world laboratory”. Results with a mean absolute percentage error (MAPE) of less than 20% when comparing biogas demand and production were consistently obtained. Full article
(This article belongs to the Special Issue Advances in Modeling Anaerobic Digestion)
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10 pages, 7221 KiB  
Article
Modeling and Simulation of Biogas Production in Full Scale with Time Series Analysis
by Celina Dittmer, Johannes Krümpel and Andreas Lemmer
Microorganisms 2021, 9(2), 324; https://doi.org/10.3390/microorganisms9020324 - 05 Feb 2021
Cited by 9 | Viewed by 3073
Abstract
Future biogas plants must be able to produce biogas according to demand, which requires proactive feeding management. Therefore, the simulation of biogas production depending on the substrate supply is assumed. Most simulation models are based on the complex Anaerobic Digestion Model No. 1 [...] Read more.
Future biogas plants must be able to produce biogas according to demand, which requires proactive feeding management. Therefore, the simulation of biogas production depending on the substrate supply is assumed. Most simulation models are based on the complex Anaerobic Digestion Model No. 1 (ADM1). The ADM1 includes a large number of parameters for all biochemical and physicochemical process steps, which have to be carefully adjusted to represent the conditions of a respective full-scale biogas plant. Due to a deficiency of reliable measurement technology and process monitoring, nearly none of these parameters are available for full-scale plants. The present research investigation shows a simulation model, which is based on the principle of time series analysis and uses only historical data of biogas formation and solid substrate supply, without differentiation of individual substrates. The results of an extensive evaluation of the model over 366 simulations with 48-h horizon show a mean absolute percentage error (MAPE) of 14–18%. The evaluation is based on two different digesters and demonstrated that the model is self-learning and automatically adaptable to the respective application, independent of the substrate’s composition. Full article
(This article belongs to the Special Issue Advances in Modeling Anaerobic Digestion)
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