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Developing the Food, Water, and Energy Nexus for Food and Energy Scenarios with the World Trade Model

Authors: Ignacio Cazcarro; Naci Dilekli;

Developing the Food, Water, and Energy Nexus for Food and Energy Scenarios with the World Trade Model

Abstract

The food, energy, and water (FEW) nexus has gained increased attention, resulting in numerous studies on management approaches. Themes of resource use, and their subsequent scarcity and economic rents, which are within the application domain of the World Trade Model, are ripe for study, with the continuing development of forward- and backward-facing economic data. Scenarios of future food and energy demand, relating to supply chains, as well as direct and indirect resource uses, are modelled in this paper. While it is possible to generate a substantial number of economic and environmental scenarios, our focus is on the development of an overarching approach involving a range of scenarios. We intend to establish a benchmark of possibilities in the context of the debates surrounding the Paris Climate Agreement (COP21) and the Green New Deal. Our approach draws heavily from the existing literature on international agreements and targets, notably that of COP21, whose application we associate with the Shared Socioeconomic Pathway (SSP). Relevant factor uses and scarcity rent increases are found and localized, e.g., on the optimal qualities of water, minerals, and land. A clear policy implication is that, in all scenarios, processes of energy transition, raw material use reduction, and recycling must be strengthened.

Countries
Russian Federation, Spain
Keywords

World Trade Model, 330, Virtual water trade, 333, factor scarcity, Water nexus, Factor uses, water nexus, TD201-500, Energy transition, virtual water trade, Energy, Water supply for domestic and industrial purposes, food, factor uses, Hydraulic engineering, Factor scarcity, energy transition, Food, TC1-978, energy

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    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).
    3
    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).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
3
Top 10%
Average
Average
Green
gold