4.7 Article

Valorization of Agricultural By-Products Within the Energyscapes: Renewable Energy as Driving Force in Modeling Rural Landscape

期刊

NATURAL RESOURCES RESEARCH
卷 28, 期 -, 页码 111-124

出版社

SPRINGER
DOI: 10.1007/s11053-018-9408-1

关键词

Agricultural by-products; Bioenergy; Rural landscape; GIS; Energyscapes

资金

  1. Project 'SMART Basilicata' [6386-3]
  2. Cohesion Fund 2007-2013 of the Basilicata Regional Authority

向作者/读者索取更多资源

Due to several growing environmental constraints, renewable energy sources currently play an increasingly crucial role that, owing to their high temporal and spatial variability, needs a careful planning approach. It is important therefore to develop a framework that examines the distribution of different energy sources in a spatio-temporal context. From an energy point of view, a regional territory, such as an internal southern Italian region (the Basilicata Region), can be considered as a paradigmatic case study, because it is characterized by significant sources of renewable energy (e.g., biomass, wind, solar, hydro) connected to its morphological and environmental structure, as well as to its agricultural and food productions. The present paper in based on an analysis of the spatial supply and relationships between renewable energy potentials and rural land, through the use of a Geographic Information System that has been implemented with the aim to analyze the energy system, as well as to optimize the valorization of biomass resources that may be still unutilized within the bioenergy production chain. This study has been carried out even to bridge the gap between energy systems modeling and landscape planning. Within this context, an Energyscape may be considered as the effect resulting on the rural landscape from a combination of the supply, demand and infrastructure for energy. This framework could be therefore a starting point for an interdisciplinary analysis able to figure out optimal solutions in decision-making processes, which duly respect the protection and restoring of endangered ecosystems, supporting the decision about an optimal spatial localization of energy plants as well.

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