What are the expected relative GHG emission savings of biofuels: uncertainty

The importance of calculating uncertainty in the case of biofuels: I have ended my last post saying that knowing uncertainty levels is important in good policy making. However, I have realized that I feel that I have not really explained this point, so I would like to do so now with this quick example.

 Figure 2.

I have found this diagram today in a presentation by Stanford University on uncertainty in biofuel production (Curtright, 2011). It focuses on the Calculating Uncertainty in Biomass Emissions (CUBE) model (figure 2), which is designed to estimate the uncertainty of all the components of the diagram in figure 2. The boxes indicated in green are the four components with the highest GHG emissions, with the two green boxes in the centre of the diagram also representing the components with the highest uncertainty levels.

These highest uncertainty levels probably arise because these components vary depending on the regional and temporal differences between sites (what the land was used for previously, organic matter availability in the soil and soil respiration rate), on what crops are grown (whether they are highly nitrogen-dependent or not, for example) and on what management techniques each individual farmer adopts (how efficiently fertilizer is applied and how intensively fossil fuel is used in cultivation). This therefore suggests that these high uncertainty levels probably arise because their management is difficult to control, as it depends on so many factors.

Identifying and understanding this uncertainty can be important to policy makers, as it shows that even if the GHG emissions from biomass conversion are the same for all biomass where the procedure has been standardized, the emissions of the biomass derived from different farmers and different areas are likely to still be very different. These uncertainty levels thus illustrate the importance of calculating emissions from biofuel that is grown at different sites separately in this case and reflect on the dangers of generalizing. Ignoring this uncertainty could lead to crude overestimates or underestimates of GHG emissions from biofuel production, while taking the uncertainty into account can allow to minimize emissions. For example, if the uncertainty is accounted for and the emissions are calculated specifically for each case, only the sites where biofuel cultivation is beneficial can be allowed to operate for the purpose.