First series of seafood datasets in ecoinvent: setting the pace for future development

• Published in: The international journal of life cycle assessment 2020-07, Vol.25 (7), p.1333-1342
• Main Authors: Avadí, Angel, Vázquez-Rowe, Ian, Symeonidis, Avraam, Moreno-Ruiz, Emilia
• Format: Article
• Language: English
• Subjects: Aquaculture; Construction; Conversion ratio; Datasets; Earth and Environmental Science; Energy consumption; Energy utilization; Environment; Environmental Chemistry; Environmental Economics; Environmental Engineering/Biotechnology; Feed conversion; Fish meal; Fisheries; Hake; Infrastructure; Life cycle analysis; Life cycle assessment; Life cycles; Modelling; Seafood; Sustainable Food Production and Consumption; Tilapia; Trout
• ISSN: 0948-3349; 1614-7502
• DOI: 10.1007/s11367-019-01659-x

Purpose The number of life cycle assessment studies related to seafood has risen considerably in the past decade. Despite this proliferation, major life cycle inventory databases tend to lack information describing this sector. Hence, the main objectives of this study are to present the first effort to aggregate and standardize seafood-related datasets in the ecoinvent database and to explain the main data sources and methodological choices used in the building of the datasets. Methods A list of the main datasets included in this first series is presented with a brief description of the underlying modelling approaches. Seafood capture, production and processing activities were modelled as the use phase of the required infrastructure. The full life cycle of infrastructure was considered, from construction, through use and maintenance to end-of-life. Results and discussion Some of the most representative seafood industries in South America were modelled, namely Peruvian anchovy and hake fisheries, Andean trout, Brazilian tilapia and Peruvian fishmeal production, as well as the production of canned, frozen, cured and of a multi-ingredient fish-based product (fish sticks). Inventory data were found to be in line with those of seafood LCA literature and driven by the parameters widely known to be critical: fuel use intensity for fisheries, feed conversion ratio for aquaculture and energy intensity for seafood processing and reduction into fishmeal. The modelling approach was modular and intuitive, thus useful and reproducible by database users and data providers. Conclusions The datasets created constitute a robust basis for the use of seafood-related data in international databases. It is expected that this work will stimulate further efforts by practitioners and data providers to model their inventory data into ecoinvent and other life cycle inventory databases.