Urban-rural bioenergy planning as a strategy for the sustainable development of inner areas: A GIS-based method to chance the forest chain

We describe the application of the spatial-based r.green.biomassfor Decision Support System (DSS), which is able to calculate the energy available from forest biomass residues, in a case study in an inner area of Italy, the Union of Pistoia Apennines Municipalities. Inner areas need strategies to counteract demographic abandonment as well as to improve socioeconomic conditions. This work considers the suitability of urban buildings to be served by biomass-energy plants as well as the supply/demand balance at the basin level. The suitability of the implementation of district-heating plants (DHP) was computed by means of a multicriteria analysis (MCA) model able to combine the following parameters: (i) yearly energy needs at the building level, (ii) building density, (iii) distance from the gas network and (iv) accessibility of the buildings/urban context. The MCA involved various experts and stakeholders to choose the parameters and to assess the weight to be assigned. A participative approach based on the Analytic Hierarchy Process (AHP) was carried out. Once DHP suitability and potential energy demand had been calculated, the basin energy density was computed. The optimal localization of DHP was then determined at the geographic level to analyze the technical and economic availability of the bioenergy supply. The new DHP implementation was analyzed for basins with both a high supply/demand ratio and high building suitability. Using the r.green.biomassfor software, the bioenergy availability was estimated from both ecological and economic points of view, while taking into account several environmental, technical, normative and financial variables. A series of scenarios have been analyzed using sensitivity analysis. The absence/presence of bioenergy production, as well as the variability of woodchip prices, stressed the high importance of wood-residue valorization for the improvement of the forest chain. The approach we tested allows for better understanding and valuation of marginal areas in which planning is more difficult because resources are unevenly distributed. By highlighting suitable basins, energy planning is focused where it is advisable. The DSS is an effective tool for planning and communicating spatially explicit results to stakeholders. Although forest biomass covers a limited amount of energy demand and must be integrated with other renewable sources, forest-biomass valorization has huge positive side effects on the energy-supply production chain and can be a driving force to revive local economies. Our spatial results confirm the validity of a holistic strategy for local development