Special Issue "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: 31 July 2021.

Special Issue Editors

Dr. Florian Centler
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Guest Editor
Department of Environmental Microbiology, Helmholtz Centre for Environmental Research—UFZ, Leipzig, Germany
Interests: systems biology; mathematical modeling; microbiomes; anaerobic digestion; microbial ecology; microbial biotechnology; bioinformatics
Dr. Denny Popp
Website
Guest Editor
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
Dr. Sören Weinrich
Website
Guest Editor
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 papers will be 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 2000 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 (1 paper)

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Research

Open AccessArticle
Modeling and Simulation of Biogas Production in Full Scale with Time Series Analysis
Microorganisms 2021, 9(2), 324; https://doi.org/10.3390/microorganisms9020324 - 05 Feb 2021
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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