Towards Standardization of Life-Cycle Metrics for Biofuels: Greenhouse Gas Emissions Mitigation and Net Energy Yield

Abstract

Despite a rapid worldwide expansion of the biofuel industry, there is a lack of consensus within the scientific community about the potential of biofuels to reduce reliance on petroleum and decrease greenhouse gas (GHG) emissions. Although life cycle assessment provides a means to quantify these potential benefits and environmental impacts, existing methods limit direct comparison within and between different biofuel systems because of inconsistencies in performance metrics, system boundaries, and underlying parameter values. There is a critical need for standardized life-cycle methods, metrics, and tools to evaluate biofuel systems based on performance of feedstock production and biofuel conversion at regional or national scales, as well as for estimating the net GHG mitigation of an individual biofuel production system to accommodate impending GHG-intensity regulations and GHG emissions trading. Predicting the performance of emerging biofuel systems (e.g., switchgrass cellulosic ethanol) poses additional challenges for life cycle assessment due to lack of commercial-scale feedstock production and conversion systems. Continued political support for the biofuel industry will be influenced by public perceptions of the contributions of biofuel systems towards mitigation of GHG emissions and reducing dependence on petroleum for transportation fuels. Standardization of key performance metrics such as GHG emissions mitigation and net energy yield are essential to help inform both public perceptions and public policy.

Uncertainty Analysis of the Life-Cycle Greenhouse Gas Emissions and Energy Renewability of Biofuels

“…in Shapouri et al (1995), Shapouri et al (2002), Liska and Cassman (2008) and Papong and Malakul (2010) 2 . In this case, negative net energy values indicate that (bio)fuel is non-renewable, while positive values indicate the fuel is renewable to a certain extent.…”

“…The results of the life-cycle study are analyzed, so that conclusions can be drawn and recommendations made, according to the scope and objectives of the study. Life-cycle studies of biofuel systems can be classified into three groups (Liska and Cassman, 2008;Cherubini and Strømman, 2011):…”

“…In fact, various indicators have been used, often with the same meaning but different definition, or inversely, e.g. overall energy efficiency (Boustead and Hancock, 1979;Boustead, 2003); energy efficiency (ADEME, 2002); gross energy requirement and net energy requirement (Wilting 1996); energy requirement (Whitaker et al, 2010); overall energy balance (Armstrong et al, 2002); energy balance (Börjesson and Tufvesson, 2011); cumulative energy demand (Huijbregts et al, 2006); input/output energy balance, cumulative energy requirement, fossil energy requirement, and renewable energy requirement (Cherubini et al, 2009); net energy use, and energy substitution efficiency (Gnansounou et al, 2009); energy ratio (Liska and Cassman, 2008;Papong and Malakul, 2010); net energy yield (Liska and Cassman 2008); and energy return on investment 1 (Poldy, 2008). In particular, Sheehan et al (1998) have used the life-cycle energy efficiency (LCEE), defined as the ratio between the biofuel energy content and the biofuel GER:…”

“…In this case, negative net energy values indicate that (bio)fuel is non-renewable, while positive values indicate the fuel is renewable to a certain extent. According to Liska and Cassman (2008) and Cherubini et al (2009), input-output ratios and primary energy requirements receive most attention when assessing the efficiency of bioenergy systems, because they provide a straightforward basis for comparison with conventional fossil fuel systems. Moreover, these metrics are usually thought as a surrogate for GHG emissions mitigation (Liska and Cassman, 2008).…”

“…According to Liska and Cassman (2008) and Cherubini et al (2009), input-output ratios and primary energy requirements receive most attention when assessing the efficiency of bioenergy systems, because they provide a straightforward basis for comparison with conventional fossil fuel systems. Moreover, these metrics are usually thought as a surrogate for GHG emissions mitigation (Liska and Cassman, 2008). Nevertheless, intensity factors do not provide a measure of the "energy productivity" of a system on a land-area basis, which should be the chosen parameter when dedicated energy crops compete with food, feed or fiber under land-availability constraints (Liska and Cassman, 2008;Cherubini et al, 2009;Cherubini and Strømman, 2011).…”