Life cycle and decision analysis of electricity production from biomass – Portugal case study

Pedro O. Loução, João P. Ribau and Ana F. Ferreira

Renewable and Sustainable Energy Reviews, 2019, vol. 108, issue C, 452-480

Abstract: The present study aims to endow decision-makers with an evaluation of the different ways to produce electricity from biomass considering their life cycle impact and energy efficiency, in order to highlight the most sustainable options. A model was developed based on a life cycle approach complemented by a sensitivity analysis, and supported by a posterior decision analysis, having the criteria of used energy per 1 MJ of electricity produced and as well as emissions of carbon dioxide, methane, nitrous oxide and solid particles. The decision analysis methods on LCA studies show to be useful in selecting the best solutions in multiple criteria decision, demonstrating particular importance in complementing the sensitivity analysis within an overall comparison between pathways. The considered technologies include wood gasification, Rankine's cycle, co-firing, black liquor gasification, biogas engine and combined cycle gas turbine, using as feedstock farmed wood, forest residues, black liquor, manure and municipal waste, in a total of eleven ways were studied. The results show that no solution have better results in all criteria comparatively, yet the proposed decision methods suggested that the best “global” pathways were the ones using manure, combined cycle using municipal waste as feedstock and forest residues gasification. The pathway that consumes less energy to produce 1 MJ of electrical energy is the cofiring using forest residues. The emissions of PM10 and PM2.5 are minimized in the pathways of Rankine cycle and IGCC with forest residue as feedstock, respectively. The sensibility analysis indicates that input values chosen can affect considerably the final results, together with the quality of the biomass.

Keywords: Biomass; Electricity; Emissions; Energy; Life cycle; Decision analysis (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1016/j.rser.2019.03.063

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