Modelling matter and energy flows of local, refined grass-clover protein feed as alternative to imported soy meal

Andreas Kamp, Morten Ambye-Jensen and Hanne Østergård

Ecological Modelling, 2019, vol. 410, issue C, -

Abstract: Trends of increasing human population, diets rich in meat, highly processed and vigorously transported products put high pressure on our ability to produce ever more food globally at the same time as supporting healthy agricultural ecosystems globally. Future food production needs to focus on optimisation of the food system in order to develop within the constraints of planetary boundaries. Modelling of energy and material flows of production systems by means of Emergy Assessment is a way to help in this task. We model and assess a hypothetical, large-scale biorefinery production from field to the provision of pig feed, biogas and fertiliser based on grass-clover mixtures (Bioref scenario). A hot spot analysis concludes that grass-clover mixture cultivation has high diesel and labour requirements, and that approximately half of the resource use (in solar emjoules, sej) in the Bioref scenario occurs during agricultural production. We find that the Bioref scenario is very labour intensive: 75% of total resource use (in sej/year) is related to labour. Next, we compare the Bioref scenario to the current provision in Denmark of soy meal imported from Brazil combined with natural gas from Denmark (Current scenario). We conclude that the Bioref production system could reduce the use of resources, reduce the dependence on non-renewable resources, significantly decrease GHG emissions from fossil fuel use, and does not need external heat input, but has higher diesel and electricity use, increased land demand and much more dependence on labour embodied in goods. Finally, we discuss different perspectives in relation to labour requirements for the two production systems.

Keywords: Biogas; Biorefinery; Feed; Grass-clover mixture; Emergy; Labour (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:410:y:2019:i:c:6

DOI: 10.1016/j.ecolmodel.2019.108738

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