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Journal of Cleaner Production
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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MCBioCH4: A computational model for biogas and biomethane evaluation

Authors: marco ravina; carlo castellana; deborah panepinto; mariachiara zanetti;

MCBioCH4: A computational model for biogas and biomethane evaluation

Abstract

Abstract The production and use of biogas and biomethane by anaerobic digestion is part of the critically needed energy transition, and it is achieving a growing interest in Europe. The planning and design of biogas/biomethane solutions necessitates the support of modelling tools for the calculation and evaluation of mass, energy and emission flows originated by different process and technological configurations. In the present study, a model for the preliminary evaluation of biogas and biomethane systems is presented. The model (named MCBioCH4) focuses on triple targets: i) obtaining information about the productivity of biogas/biomethane plants regarding achievable gas flow rates; ii) determining the plant energy expenditures and subsequently the economically exploitable energy flow shares; and iii) assessing the entire environmental impact of the system. The design of MCBioCH4 was specifically addressed to dual objectives: i) provide support to the preliminary assessment and comparison of different potential plant configurations and technological solutions, and ii) assist users in the complete definition of mass, energy and environmental flows, through the implementation of default datasets and assisted data input. The model is a standalone application fully equipped with graphical user interfaces. A set of default parameters was implemented in MCBioCH4, based on a detailed literature review. Alternatively, customized input parameters may be introduced by the user. If biogas scenarios are selected, the model simulates a combustion in a cogeneration unit. If biomethane scenarios are selected, the user is allowed to define the type and features of the upgrading technology. Two different options are implemented for biomethane: injection to the natural gas distribution grid, or use as a transportation fuel. The emission of carbon dioxide equivalent associated to each phase of the process is estimated by the model, based on a cradle-to-grave approach. Default emission factors are available, but these can be customized by the user. MCBioCH4 was tested on a case study in Italy. It provides a valuable support to project developers and administrations in defining the most economically and environmentally sustainable plant configurations.

Country
Italy
Related Organizations
Keywords

Bioenergy; Biogas modelling; Biomethane upgrading; CO ; 2; equivalent ; Greenhouse gas emission

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    16
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Average
Top 10%
Green