The PBF project aims to answer the lack of specific tool to assess the impact of different products on biodiversity. In order to do this, baseline principle of the PBF project is to co-develop a method and a tool crossing biodiversity studies and companies’ data to quantify the impacts of a product on biodiversity all along the product’s life cycle stages in order to provide recommendations for changes. PBF project brings together all existing available data and provide quantitative results for decision making processes regarding product strategy (risks analysis, purchasing strategy, eco-design…).
The main objective of the project is to improve environmental performance of a product by identifying environmental hotspots that can be improved and support eco-design approaches. In order to have such a capacity the PBF should have a strong discriminating capacity: the method aims to distinguish between the variants of a product the one with lower impacts on biodiversity.
The LCA framework is used to product the relative differences between the variants of a product. In the long term, it will also allow to compare different products or different sectors at larger scales.
To be useful for companies, the method has to be integrated in the LCA ecosystem, meaning be connected to LCA database and compared to current method results. Therefore, the choice made for PBF method is to include biodiversity knowledge in the LCA framework, in accepting that the LCA historical framework can be modified if necessary.
The latest LCA developments are used to be at the cutting edge of the LCA ecosystem.
The method aims to cover the 5 pressures on biodiversity identified in the Millennium Ecosystem Assessment (2005): land use (habitat change), pollutions, climate change, invasive species, overexploitation of species.
Biodiversity knowledge included in the LCA framework is based on ecological publications specific for each pressure and on available global biodiversity database to assess the state of biodiversity.
Several scientific challenges are associated with this project, especially regarding the definition of relevant indicators for each pressure and relevant spatial scales, and the use of heterogeneous data. This approach is tested on three case studies in the project (food, textile and cosmetic industries).