Til innholdet

Prosjektnummer

901334

Prosjektinformasjon

Prosjektnummer: 901334
Status: Avsluttet
Startdato: 01.01.2017
Sluttdato: 31.01.2018

Seafood LCI database: A key to achieve more sustainable seafood production

Key project achievements
• A methodology for collecting data for a seafood LCI database has been developed. This method includes what data that is needed to model seafood related processes in a LCA.
• A number of existing pilot datasets have been collected using this methodology and published for integration in existing databases.
• A plan for how the industry can extend the database to cover the most important types of seafood including feed inputs has been developed.

Results achieved
Summary of results from the project’s final reporting
The developed methodology will serve as guidelines for anyone who wants to collect and contribute data for seafood to LCI databases. It describes relevant data to collect for each step in the supply chain specifically for seafood production up until preparation (defined as cutting and cooling in accordance with EU regulations, sometimes termed primary processing, to distinguish from processing which transforms the product through e.g. canning, smoking, marinating, salting, drying or mixing with other ingredients). No minimum quality level is defined, but requirements to document quality and representativity are described and data entries are classified as shall or may, depending on importance.

The importance obviously also depends on the impacts studied in a study using the data, therefore it has to be decided from case to case whether data is of sufficient quality for the purpose of the study and to be able to do this, proper documentation is critical. A suggested nomenclature is also provided that is easy to use and makes sense from a production point of view.

The datasets now provided, represent both major targeted reduction fisheries (Anchoveta and Gulf menhaden) and fisheries for human consumption where trimmings are used to produce fish meal and oil or silage (herring, mackerel and cod).

The outlined methodology together with the pilot datasets provide a very useful starting ground and guideline for the industry to initiate a more widespread collection of datasets. The alignment and integration with initiatives such as the GFLI and EU PEF-CR will be critical. Other issues to solve will be the hosting and strategy for continuous update of seafood LCI data.

Resultatene og metodene utviklet i dette prosjektet vil øke kvaliteten og redusere kalkulasjonskostnadene ved implementering av en LCI Seafood database. Dette gjelder både for selskaper i sjømatnæringen, akademia og andre.
Background
There is a great need to lower the environmental impact of fisheries and aquacultural production systems. Environmental legislation, labels, investors, supplier policies and consumers are shifting towards a more holistic view where the whole life cycle and all types of environmental impacts are taken into account, and this is also seen by companies as a key to remain competitive. This can be done by (but is not limited to) developing scientifically based environmental footprints (EF) of products in the supply chain, to be used by actors in the supply chain for guiding in both improving internal operations and sustainable sourcing of raw materials. The EFs can also be used in marketing activities, where the producers with the highest performing products stand out, and they can be used to compare seafood products with other food products.

The Norwegian seafood industry delivers high quality products with a high environmental performance, and also has a well developed infrastructure and a high education level. This means that the industry will benefit from the increased environmental transparency and is well prepared to implement it and comply with future policies. The EFs are calculated by using Life Cycle Assessment (LCA) methodology and data, but currently there is a lack of proper data. This project aims to lay the foundation that will make the data available, which can be used in a wide variety of applications within the field of LCA.
Objectives
Main objective
To develop the blueprints for a Seafood LCI database.

Sub-objectives
• To develop a methodology including e.g. a detailed scope description and processes for developing and publishing datasets.
• To specify the technical infrastructure of the database.
• To produce and publish at least six datasets.
• To integrate the datasets in the Agri-Footprint database.
• To write a proposal on how to implement the infrastructure, processes and funding in order to scale it up and establish a long term supply of relevant LCI data.
Expected project impact
The project blueprints will be used to implement a Seafood LCI database, which will be used to publish seafood LCI datasets. It will increase the quality of footprint calculations and also lower calculation costs and increase its usefulness.

The data will be useful to LCA practitioners that can save time on data collection, but indirectly anyone that uses LCA results in any way will benefit from the data. Companies can use the data to improve their operations and to market their environmental high performance products. Small and medium-sized enterprises and startups that usually lack the means to purchase or collect data will benefit from the data since it is free. Policy makers can use both the results as a guide to set targets but also use the data as a base for establishing frameworks such as the PEF tool. Academia can use the data for research and the database to publish their results etc. The data and the EFs are considered to be an important contribution in acheiving both a sustainable production and consumption.
Project design and implementation
The project group consists of Blonk Consultants, Dalhousie University, SINTEF Fisheries and Aquaculture, and SP Technical Research Institute of Sweden. There is also a reference group which is used for the project group to get feedback on the work and to help out with any problem that could occur, but also to maintain the communication with Global Feed LCA Institute (GFLI).
 
The project consists of several activities, where the main ones are to develop a database methodology (SP, SINTEF, Blonk), specify an infrastructure (SP), dataset development (SP, Blonk, SINTEF) and integration of data in the Agri-Footprint database (Blonk). Each of the activities have deliverables and work meetings that are planned based on the activity work. A first detailed plan of meetings is made in the kickoff meeting, where also meetings with the reference group are planned and decided with the reference group. Every activity also delivers a status report to the reference group, together with the deliverable. Since the project group is relatively small a series of pulse meetings will be held frequently throughout the project with all project members. The meetings will serve to monitor the status of the work, facilitate the work and to identify possible problems that can occur. In the end of the project one adminstrative and one technical report are delivered to The Norwegian Seafood Research Fund (FHF).
Dissemination of project results
The produced datasets will be accessible online, together with the methodology document and the plan for the second phase, i.e. to implement the database. Information of the project will be relayed via the existing communication channels of the particpating organisations, e.g. newsletters, web sites, networks etc.
keyboard_arrow_up