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Third generation algae biofuels in Italy by 2030: A scenario analysis using Bayesian networks

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  • Gambelli, Danilo
  • Alberti, Francesca
  • Solfanelli, Francesco
  • Vairo, Daniela
  • Zanoli, Raffaele

Abstract

We have analysed the potential for biofuels from microalgae in the Italian biofuels context. This scenario analysis considers alternative pathways for the adoption of biofuels from microalgae by the year 2030. The scenarios were developed using a probabilistic approach based on Bayesian networks, through a structured process for elicitation of expert knowledge. We have identified the most and least favourable scenarios in terms of the expected likelihood for the development of the market of biofuels from microalgae, through which we have focussed on the contribution of economic and policy aspects in the development of the sector. A detailed analysis of the contribution of each variable in the context of the scenarios is also provided. These data represent a starting point for the evaluation of different policy options for the future biofuel market in Italy. The best scenario shows a 75% probability that biofuels from microalgae will exceed 20% of the biofuel market by 2030. This is conditional on the improvement and development of the technological changes and environmental policies, and of the markets for bioenergy and novel foods derived from microalgae.

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  • Gambelli, Danilo & Alberti, Francesca & Solfanelli, Francesco & Vairo, Daniela & Zanoli, Raffaele, 2017. "Third generation algae biofuels in Italy by 2030: A scenario analysis using Bayesian networks," Energy Policy, Elsevier, vol. 103(C), pages 165-178.
  • Handle: RePEc:eee:enepol:v:103:y:2017:i:c:p:165-178
    DOI: 10.1016/j.enpol.2017.01.013
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    4. Bharathiraja, B. & Iyyappan, J. & Gopinath, M. & Jayamuthunagai, J. & PraveenKumar, R., 2022. "Transgenicism in algae: Challenges in compatibility, global scenario and future prospects for next generation biofuel production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    5. Gupta, Jharna & Agarwal, Madhu & Dalai, A.K., 2019. "Intensified transesterification of mixture of edible and nonedible oils in reverse flow helical coil reactor for biodiesel production," Renewable Energy, Elsevier, vol. 134(C), pages 509-525.
    6. Huang, Zhiming & Yang, Lin & Jiang, Wen, 2019. "Uncertainty measurement with belief entropy on the interference effect in the quantum-like Bayesian Networks," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 417-428.
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    8. Arkadiusz Piwowar & Maciej Dzikuć, 2019. "Development of Renewable Energy Sources in the Context of Threats Resulting from Low-Altitude Emissions in Rural Areas in Poland: A Review," Energies, MDPI, vol. 12(18), pages 1-15, September.

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