A life cycle inventory of microalgae-based biofuels production in an industrial plant concept. (February 2020)

• Record Type: Journal Article
• Authors: Branco-Vieira, M.; Costa, D.; Mata, T.M.; Martins, A.A.; Freitas, M.A.V.; Caetano, N.S.
• Is Part Of: Energy reports. Volume 6(2020)Supplement 1
• Page Start: 397
• Page End: 402
• Publication Date: 2020-02
• Subjects: Biofuels -- Life Cycle Assessment (LCA) -- Life Cycle Inventory (LCI) -- Microalgae -- Phaeodactylum tricornutum; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2019.08.079
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: Microalgae have been reported as a promising alternative for biofuels production. However, the use of microalgae for biofuels is still a challenge due to the intense energy use and the generation of a significant amount of biomass residues in the process. In order to analyze the environmental impacts of different technological processes for the production of biodiesel from microalgae, several studies have been published making use of the Life Cycle Assessment (LCA) methodology, which allows the recognition of the process bottlenecks and supports the identification of alternatives for a more efficient use of the feedstock. Therefore, in this study, a Life Cycle Inventory (LCI) is compiled, based on real pilot-scale process data, which was scaled-up to a microalgae biomass industrial plant for biofuel production. Values of energy, nutrients, water, and materials consumption are used to create an inventory of inputs and outputs for biomass cultivation and biodiesel production, in order to acquire data to conduct a complete LCA modeling in future studies. According to this model, to produce 1 kg of biodiesel it is necessary about 12 kg of dried algae biomass. This study supports the decision-making process in biofuel production to promote the development of sustainable pilot and large-scale algae-based industry, through the identification of critical factors.