Contribution of energy crops to the bioenergy sector in Tuscany: development of a GIS-based forecasting model

Abstract

The adopted methodology, based on the development of a vector geodatabase integrated with a database 
management system (PostgreSQL), allowed to produce  a dynamic and versatile simulation model. The modelling tool developed is capable of providing results with high spatial definition (intersection of vector layers) by defining several information layers at a time, following criteria and rules set by the user. The model allows to evaluate different scenarios by defining: i) factors affecting crop adaptability to soil and climate conditions; ii) land use categories hypothetically involved in energy crops cultivation; iii) proportion of the available land area hypothetically involved. In the proposed scenario, a realistic introduction rate of lignocellulosic energy crops and biofuel crops within the agricultural context of Tuscany was simulated. In fact, 10% of the allocable area (non-irrigated arable lands with 15% maximum slope) were assigned to lignocellulosic and 20% of the remaining area to biofuel crops. Results show the differences in terms of crops adaptation to geophysical factors, highlighting the possibility of assigning suitable crops combinations to the different agricultural areas of the region. Our estimations showed that, among the lignocellulosic crops evaluated, giant reed has the largest spreading potential at spatial scale, while among the biofuel crops considered, sunflower and rapeseed were those with the highest expansion potential. Energy crops production, as estimated according to the described scenario, could reduce Tuscany region’s dependence on electricity import, helping to meet PIER (regional energy plan) targets for 2020, in terms of  potential energy production from biomass.