Although aggressive renewable energy policies have allowed for the immense growth of the biofuel industry, they have also exhausted surplus agricultural feedstocks and subsequently contributed to rapid commodity price increases in crops such as corn, soybeans, and rapeseed. However, simplistic yield tables frequently used to project the success of biofuel feedstocks fail to consider their geographic location and can overestimate yields by up to 100% (Johnston et. al, 2009). With new spatially-explicit global agricultural datasets—M3 cropland datasets— as well as more accurate yield conversion methods, scientists are able to better describe total global biofuel production, and thus more accurately predict its potential as a sustainable energy source.—Elena Davert
Johnston, M., Foley, J.Al, Holloway, T., Kucharik, C. Monfreda, C., 2009. Resetting global expectations from agricultural biofuels. Environmental Research Letters, 4 014004 (1-9).
While some may address the vast potential of alternative biofuels, such as cellulosic-ethanol and algae-biodiesel, agricultural-based biofuels are the only profitable alternatives to liquid fossil fuels that can currently be produced in large enough volumes. It is for this reason that the study of agricultural biofuel reliance has become so prevalent in the scientific community as well as in the media. In order to make the information about biofuels more accessible, yield tables have become crucial translating complex differences between chemical breakdowns of multiple crops into simplistic illustrations of their potential fuel volumes. However, it is often the case that single yield estimates for a unique location are applied to global models, and specific units are not always appropriate for comparing different crops. Unfortunately, despite these doubts, these yield ﬁgures are so heavily relied on in scientific journals, policy reports, and even media articles, that many assume that the frequency with which the values are cited corresponds to their accuracy.
This recent study combats these faults by producing the most comprehensive report to date of biofuel production potential by including crop area and yield statistics drawn from over 22,000 agricultural surveys, censuses, and statistical databases. Statistical datasets for ten ethanol crops (barley, cassava, maize, potato, rice, sorghum, sugarbeet, sugarcane, sweet potato, and wheat) and ten biodiesel crops (castor, coconut, cotton, mustard, oil palm, peanut, rapeseed, sesame, soybean, sunﬂower) were analyzed across 238 countries, territories and protectorates, then converted to standardized units of liters-per-hectare. This standardization was achieved by multiplying current agricultural yields, percent oil content, and oil densities for each crop, as well as factoring in constant processing ratios and refining factors specific to different regions.
Compared to earlier biofuel yield tables, this detailed agricultural analysis can infer that previous reports overestimated yields by 100% or more. Barley, cassava, castor, maize, rapeseed, and sunﬂower all show that previous global biofuel yields were overestimated by at least 100%, with wheat–ethanol and groundnut–biodiesel estimates having been overestimated by 150% or more. By confirming that previously accepted biofuel yield estimates are highly unrealistic, the study hopes to highlight the actual cost-benefit consequences of expanding cropland dedicated to its production. Resetting the expectations for global agricultural biofuel production and the required technology is important from en environmental standpoint because it will help more accurately frame the allocation of funding for alternative energy research.