Life cycle assessment needs predictive spatial modelling for biodiversity and ecosystem services

Rebecca Chaplin-Kramer (), Sarah Sim, Perrine Hamel, Benjamin Bryant, Ryan Noe, Carina Mueller, Giles Rigarlsford, Michal Kulak, Virginia Kowal, Richard Sharp, Julie Clavreul, Edward Price, Stephen Polasky, Mary Ruckelshaus and Gretchen Daily
Additional contact information
Rebecca Chaplin-Kramer: Natural Capital Project, Woods Institute for the Environment, Stanford University
Sarah Sim: Unilever Safety and Environmental Assurance Centre, Unilever R&D
Perrine Hamel: Natural Capital Project, Woods Institute for the Environment, Stanford University
Benjamin Bryant: Natural Capital Project, Woods Institute for the Environment, Stanford University
Ryan Noe: Natural Capital Project, Institute on the Environment, University of Minnesota
Carina Mueller: Unilever Safety and Environmental Assurance Centre, Unilever R&D
Giles Rigarlsford: Unilever Safety and Environmental Assurance Centre, Unilever R&D
Michal Kulak: Unilever Safety and Environmental Assurance Centre, Unilever R&D
Virginia Kowal: Natural Capital Project, Woods Institute for the Environment, Stanford University
Richard Sharp: Natural Capital Project, Woods Institute for the Environment, Stanford University
Julie Clavreul: Unilever Safety and Environmental Assurance Centre, Unilever R&D
Edward Price: Unilever Safety and Environmental Assurance Centre, Unilever R&D
Stephen Polasky: Natural Capital Project, Institute on the Environment, University of Minnesota
Mary Ruckelshaus: Natural Capital Project, Woods Institute for the Environment, Stanford University
Gretchen Daily: Natural Capital Project, Woods Institute for the Environment, Stanford University

Nature Communications, 2017, vol. 8, issue 1, 1-8

Abstract: Abstract International corporations in an increasingly globalized economy exert a major influence on the planet’s land use and resources through their product design and material sourcing decisions. Many companies use life cycle assessment (LCA) to evaluate their sustainability, yet commonly-used LCA methodologies lack the spatial resolution and predictive ecological information to reveal key impacts on climate, water and biodiversity. We present advances for LCA that integrate spatially explicit modelling of land change and ecosystem services in a Land-Use Change Improved (LUCI)-LCA. Comparing increased demand for bioplastics derived from two alternative feedstock-location scenarios for maize and sugarcane, we find that the LUCI-LCA approach yields results opposite to those of standard LCA for greenhouse gas emissions and water consumption, and of different magnitudes for soil erosion and biodiversity. This approach highlights the importance of including information about where and how land-use change and related impacts will occur in supply chain and innovation decisions.

Date: 2017
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DOI: 10.1038/ncomms15065

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