Natural biotic resources in LCA: Towards an impact assessment model for sustainable supply chain management

Natural resources, biotic and abiotic, are fundamental from both the ecological and socio-economic point of view, being at the basis of life-support. However, since the demand for finite resources continues to increase, the sustainability of current production and consumption patterns is questioned both in developed and developing countries. A transition towards an economy based on biotic renewable resources (bio-economy) is considered necessary in order to support a steady provision of resources, representing an alternative to an economy based on fossil and abiotic resources. However, to ensure a sustainable use of biotic resources, there is the need of properly accounting for their use along supply chains as well as defining a robust and comprehensive impact assessment model. Since so far naturally occurring biotic resources have gained little attention in impact assessment methods, such as life cycle assessment, the aim of this study is to enable the inclusion of biotic resources in the assessment of products and supply chains. This paper puts forward a framework for biotic resources assessment, including: i) the definition of system boundaries between ecosphere and technosphere, namely between naturally occurring and man-made biotic resources; ii) a list of naturally occurring biotic resources which. have a commercial value, as basis for building life cycle inventories (NOBR, e.g. wild animals, plants etc); iii) an impact pathway to identify potential impacts on both resource provision and ecosystem quality; iv) a renewability-based indicator (NOBRri) for the impact assessment of naturally occurring biotic resources, including a list of associated characterization factors. The study, building on a solid review of literature and of available statistical data, highlights and discusses the critical aspects and paradoxes related to biotic resource inclusion in LCA: from the system boundaries definition up to the resource characterization. (C) 2017 The Authors. Published by Elsevier Ltd.