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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Oconnell, Deborah
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (5/5 displayed)
- 2018Approach and methods for co-producing a systems understanding of disaster: Technical Report Supporting the Development of the Australian Vulnerability Profile
- 2015Quantifying spatial dependencies, trade-offs and uncertainty in bioenergy costs: an Australian case study (2) – National supply curvescitations
- 2015The Resilience, Adaptation and Transformation Assessment Framework: From Theory to Application
- 2012An assessment of biomass for bioelectricity and biofuel, and for greenhouse gas emission reduction in Australiacitations
- 2008Electrical, structural, and chemical properties of HfO₂ films formed by electron beam evaporationcitations
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article
Quantifying spatial dependencies, trade-offs and uncertainty in bioenergy costs: an Australian case study (2) – National supply curves
Abstract
aA biophysically constrained economic analysis of several alternative prospective pathways for biofuel production in Australiafrom crop residues (stubble), a lignocellulosic feedstock develops. N national supply cost curves are developed. As well as considering biofuels suitable for replacing the fuels currently used in land (and sea) transport suitable biofuels, we also consider electricity, and aviation biofuels.In a companion paper (1), bBiofuel production costs, dependent onhave been estimated as a function of the spatial concentration of available feedstock, are derived in a companion paper by selecting a cost minimising production scale that trades off processing and transport costs. Lower concentrations correspond to smaller processing plants, larger and greater collection areas, and greater costs. These biofuel costs are not calculated by a priori assumption of processing plant size, such as that based on scales at which similarly-produced fossil-based fuels are competitive in the contemporary economic environment. Instead they are based on minimising regional production cost by trading off between processing and transport costsOver the spatial scales corresponding to those within the collection areas required for least cost supply, variation in the concentration of crop residue feedstock is quite modest. From any Any given candidate production plant location, can be associated with a collection distance area can easily be found that approximates the least cost distance for itsthe average spatial concentration within the associated collection area, because feedstock concentration varies only modestly within cost minimising area scales. This permits the identification of aA set of plant locations, scales,, each associated with an and approximately near to least-cost collection areas is found, that in aggregate collectively service all the available feedstock. Corresponding national supply cost curves that are derived from such analysis are then also close to least cost. We apply the above approachThis is applied to Australian data, generating upper and lower bounds on nationally aggregated supply cost curves.In practice, tThe sizing of biofuel production facilities is also likely influenced by severalwill be also affected by investment scale commercial considerations including such as the reliability of feedstock supply and investor appetite for risk:, both of which also depend on investment scale. These latter issues these are discussed in a qualitatively manner.