Vol. 66 No. 4 (2011):
Special section

Agro-energy districts planning.An analysis model for the Tuscany Region

Iacopo Bernetti
Dipartimento di Economia, Ingegneria, Scienze e Tecnologie Agrarie e Forestali (DEISTAF), Sezione Economia Agraria e Forestale ed Estimo, Università degli Studi di Firenze. P.le delle Cascine 18, 50144 Firenze.
Christian Ciampi
Dipartimento di Economia, Ingegneria, Scienze e Tecnologie Agrarie e Forestali (DEISTAF), Sezione Economia Agraria e Forestale ed Estimo, Università degli Studi di Firenze. P.le delle Cascine 18, 50144 Firenze.
Sandro Sacchelli
Dipartimento di Economia, Ingegneria, Scienze e Tecnologie Agrarie e Forestali (DEISTAF), Sezione Economia Agraria e Forestale ed Estimo, Università degli Studi di Firenze. P.le delle Cascine 18, 50144 Firenze.
Augusto Marinelli
Dipartimento di Economia, Ingegneria, Scienze e Tecnologie Agrarie e Forestali (DEISTAF), Sezione Economia Agraria e Forestale ed Estimo, Università degli Studi di Firenze. P.le delle Cascine 18, 50144 Firenze.

Published 2011-08-30

Keywords

  • agro-energy district,
  • energy planning,
  • biomass,
  • spatial clustering

Abstract

European directives on energy policy promote the use of renewable resources as an alternative to traditional fossil fuels. Part of the current energy demand can be satisfied through the transformation of agro-forestry biomass sources. However, this process requires careful analysis of the resources in order to ensure the realization of sustainable local supply chains. The identification of agro-energy districts seems to be a useful first step to proper regional planning. In this framework it is very important to define techniques for the identification of homogeneous agro-energy areas. The first result of this work was the creation of an indicator set (economic, social and environmental) to assess the agro-energy vocation of the regional context. This identification was preparatory to the choice of a regionalization model, which allows a correct and consistent use of indicator sets. According to the result of this model, it is possible to define potential districts based both on their agro-energy supply/demand ratio and socioeconomic and environmental characteristics.