The effect of spatial variables on the economic and environmental performance of bioenergy production chains

The effect of spatial variables on the economic and environmental performance of bioenergy production chains

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Article ID: iaor20113819
Volume: 131
Issue: 1
Start Page Number: 224
End Page Number: 233
Publication Date: May 2011
Journal: International Journal of Production Economics
Authors: , , ,
Keywords: economics
Abstract:

The aim of this paper is to understand the impacts of spatial variables on the performance of bioenergy production chains (BPCs). Even though the strong debates continue on the use of first generation biomass for bioenergy production, many countries continue to utilize it as an alternative energy source. Several studies have been carried out on biomass transformation efficiency, on environmental impacts of using crop in biofuel production, and on its negative effects on increasing food prices. However, less attention has been paid to the role played by the spatial variables on the performance measures of BPCs. Results show that higher land dispersion degree and less area accessibility levels reduce the economic and environmental performance of the BPCs. The construction of the energy‐balanced chain reduces the negative environmental impacts caused by fossil energy use in the processes of the BPC. Managerial implications can also be obtained from actual case study about the biodiesel plant location decisions. In this paper, we analyse how three spatial variables, i.e. cultivation area size, land dispersion, and accessibility to cultivation areas, can affect the performance of energy‐balanced BPC, which produces its own electric and thermal energy demand. The chain is represented as a network of processes, where all inputs and outputs are geographically referred and analysed in a theoretical case example. We propose an enterprise input–output (EIO) model, which can be used as an accounting tool to compute the main materials and energy flows‐related costs and as a planning tool to evaluate the chain performance in different scenarios. Finally, the proposed model is applied to an actual case study, to investigate the opportunity to establish a sunflower‐based BPC in Apulia region (Italy) and to assess its performance.

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