Life cycle assessment needs predictive spatial modelling for biodiversity and ecosystem services
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 methodo...
Gespeichert in:
Veröffentlicht in: | Nature communications 2017-04, Vol.8 (1), p.15065-15065, Article 15065 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | 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.
Life cycle assessments are used by corporations to determine the sustainability of raw source materials. Here, Chaplin-Kramer
et al
. develop an improved life cycle assessment approach incorporating spatial variation in land-use change, and apply this framework to a bioplastic case study. |
---|---|
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/ncomms15065 |