Developments in Bioelectricity and Perspectives in Italy: An Analysis of Regional Production Patterns

Andrea Savio, Giovanni Ferrari, Francesco Marinello, Andrea Pezzuolo, Maria Cristina Lavagnolo and Mariangela Guidolin ()
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Andrea Savio: McDonough School of Business, Georgetown University, Washington, DC 20057, USA
Giovanni Ferrari: Department of Land, Environment, Agriculture and Forestry, University of Padua, 35020 Legnaro, Italy
Francesco Marinello: Department of Land, Environment, Agriculture and Forestry, University of Padua, 35020 Legnaro, Italy
Andrea Pezzuolo: Department of Land, Environment, Agriculture and Forestry, University of Padua, 35020 Legnaro, Italy
Maria Cristina Lavagnolo: Department of Civil, Environmental and Architectural Engineering, University of Padua, 35131 Padua, Italy
Mariangela Guidolin: Department of Statistical Sciences, University of Padua, Via C. Battisti 241, 35123 Padua, Italy

Sustainability, 2022, vol. 14, issue 22, 1-25

Abstract: Bioenergy is being increasingly used worldwide to generate energy from biogas, biomethane, and other biofuels, bringing significant environmental and economic benefits. In Italy, biogas can significantly contribute to the achievement of the renewable energy targets set at the national and European levels. The exploitation of this energy source in a particular area is determined by its environmental and anthropic properties, as well as by the incentive system and the political will of decision makers. This paper analyzes the socioeconomic drivers and natural conditions triggering bioelectricity production in Italian regions. The analysis proposed here was performed in two steps—first, by identifying groups of similar regions for some natural, social, and economic variables, and then by modeling the historical trajectory of bioelectricity production for each identified group with innovation diffusion models. As a general finding, regions pertaining to the same group in terms of natural and socioeconomic conditions revealed a similar production pattern for bioelectricity, as confirmed by the results of diffusion modeling. On the basis of the diffusion modeling procedure, some scenario simulations were performed, which suggested the set-up of suitable policy actions for each group of regions.

Keywords: bioelectricity; bioenergy; regional production; cluster analysis; innovation diffusion modeling; scenario simulations (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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