On quantifying sources of uncertainty in the carbon footprint of biofuels: crop/feedstock, LCA modelling approach, land-use change, and GHG metrics

Document Type : Research Paper


1 Department of Sustainable Development, Environmental Science and Engineering (SEED), School of Architecture and the Built Environment (ABE), KTH - Royal Institute of Technology, Sweden.

2 Department of Operations Analytics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

3 Institute of Environmental Sciences, Leiden University, Leiden, The Netherlands.

4 NSW Department of Primary Industries, University of New England, Armidale, Australia.


Biofuel systems may represent a promising strategy to combat climate change by replacing fossil fuels in electricity generation and transportation. First-generation biofuels from sugar and starch crops for ethanol (a gasoline substitute) and from oilseed crops for biodiesel (a petroleum diesel substitute) have come under increasing levels of scrutiny due to the uncertainty associated with the estimation of climate change impacts of biofuels, such as due to indirect effects on land use. This analysis estimates the magnitude of some uncertainty sources: i) crop/feedstock, ii) life cycle assessment (LCA) modelling approach, iii) land-use change (LUC), and iv) greenhouse gas (GHG) metrics. The metrics used for characterising the different GHGs (global warming potential-GWP and global temperature change potential-GTP at different time horizons) appeared not to play a significant role in explaining the variance in the carbon footprint of biofuels, as opposed to the crop/feedstock used, the inclusion/exclusion of LUC considerations, and the LCA modelling approach (p<0.001). The estimated climate footprint of biofuels is dependent on the latter three parameters and, thus, is context-specific. It is recommended that these parameters be dealt with in a manner consistent with the goal and scope of the study. In particular, it is essential to interpret the results of the carbon footprint of biofuel systems in light of the choices made in each of these sources of uncertainty, and sensitivity analysis is recommended to overcome their influence on the result.

Graphical Abstract

On quantifying sources of uncertainty in the carbon footprint of biofuels: crop/feedstock, LCA modelling approach, land-use change, and GHG metrics


  • Uncertainty in the carbon footprints of biofuels is large.
  • Uncertainty comes from crop used, LUC and LCA modelling, but not GHG metrics.
  • Uncertain parameters should be dealt with consistently with the goal and scope.
  • Results should be interpreted in light of the methodological choices made.
  • Sensitivity analysis is recommended.


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