Uncertainty analysis of the environmental sustainability of biofuels

Abstract

Background Faced with a changing climate, bioenergy has been promoted as a sustainable resource. However, while it is a renewable energy source, biofuel cultivation comes with several environmental problems such as land use change and water consumption, the environmental impacts of which often counterbalance the reduced global warming potential compared to fossil alternatives. Methods This paper presents life cycle assessment (LCA) results for greenhouse gas (GHG) emissions (carbon footprints) and water consumption (water scarcity footprint) for different first-generation biofuels in comparison with their fossil alternatives. We employed standard (secondary) LCA data including uncertainties of process activities, resource consumption, and emissions throughout the value chain in order to compare different options under the influence of uncertainties and in order to identify the contribution to variance (CTV) of input data, giving insight into which environmental flows need to be better assessed. Furthermore, by also introducing uncertainties in the impact assessment for GHG emissions and water consumption, we were able to determine which LCA stage is more influenced by uncertainties, the accounting or impact assessment stage. Additionally, we analyzed the effect of choosing different time horizons GHGs (typically set to 100 years). Results The analyzed fuels perform differently depending on the choice of impact category considered. For liquid fuels, we observed a tradeoff between resource depletion and water footprint, while biogas options have lower impacts in most categories. Biogas from waste has significantly lower carbon footprints than natural gas for long time horizons and a similar water footprint. However, with the 20-year Intergovernmental Panel on Climate Change (IPCC) factors, methane emissions from biogas largely compensate the fossil CO2 emissions in our case and no robust difference is observed under uncertainty considerations. Both impact assessment and inventory uncertainties are important. Due to the very high number of parameters, the CTV analysis was not robust for assessing GHG emissions. Conclusions This study shows that uncertainty is important in LCA and carbon or water footprint assessment of agricultural feedstock production. Integration of parameter uncertainties helps to evaluate the significance of the difference from two product options. For biogas, the choice of the time horizon in carbon footprint assessment is decisive and needs a strong justification.