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Increasing Biowaste and Manure in Biogas Feedstock Composition in Luxembourg: Insights from an Agent-Based Model

Authors: Alper Bayram; Antonino Marvuglia; Maria Myridinas; Marta Porcel;

Increasing Biowaste and Manure in Biogas Feedstock Composition in Luxembourg: Insights from an Agent-Based Model

Abstract

Biowaste and manure are resources readily available as feedstock for biogas production. Possible scenarios with increased use of biowaste and manure for biogas production in the Grand Duchy of Luxembourg are investigated in this study using an Agent-Based Model (ABM) coupled with Life Cycle Assessment (LCA). ABMs are particularly suitable to simulate human-natural systems, since they allow modelers to consider behavioral aspects of individuals. On the other hand, when it comes to the assessment of a system’s environmental sustainability, LCA is largely recognized as a sound methodology and widely used in research, industry, and policy making. The paper simulates three different scenarios that reproduce 10 years and can help policymakers building emission mitigation strategies. The aim is to increase the number of biogas plants or change the feedstock composition for anaerobic digestion in Luxembourg whilst observing the expected environmental impacts generated by these changes. The first scenario (Scenario A) is the baseline scenario, which simulates the current situation, with 24 operating biogas plants. The results of Scenario A show that, on average, 63.02 GWh of electricity production per year is possible from biogas. The second scenario (Scenario B) foresees an increase in the manure share (which is initially 63%) in the biogas feedstock composition along with an increase in the number of biogas production plants. The third scenario (Scenario C) only concerns increasing the amount of manure in the feedstock composition without the introduction of new plants. The results of Scenario C show that an 11% increase in electricity production is possible if more farms contribute to the production by bringing their excess manure to the biogas plant. This value is even higher (14%) in Scenario D where more biowaste is made available. The aggregated life-cycle impact assessment (LCIA) single scores, calculated with the ReCiPe method, show that Scenario C has the lowest impacts (although by only around 7% compared to the worst performing scenario, i.e., Scenario D), while Scenario D allows the highest electricity production (71.87 GWh in the last year of the simulation). As a result, the inclusion of more livestock farms into already established biogas cooperatives (as in Scenario C) can pave the way for an increase in electricity production from renewables and can bring a reduction in environmental impacts (more than 35% for the Terrestrial Ecotoxicity impact category and more than 27% in categories such as Agricultural Land Occupation, Marine Eutrophication and Water Depletion), thanks to the exploitation of manure for biogas production.

Keywords

Environmental effects of industries and plants, TJ807-830, biogas; life cycle assessment; enteric fermentation; green consciousness; sustainable agriculture, TD194-195, Renewable energy sources, sustainable agriculture, Environmental sciences, life cycle assessment, biogas, green consciousness, GE1-350, enteric fermentation

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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!
0
Average
Average
Average
gold