Indirect Effects Negate Global Climate Change Mitigation Potential of Substituting Gasoline With Corn Ethanol as a Transportation Fuel in the USA

Abstract

Concerns over climate change have led to the promotion of biofuels for transport, particularly biodiesel from oilseed crops and ethanol from sugar and starch crops. However, additional concerns arose on whether the climate change mitigation potential of biofuels is negated by the associated direct land requirements (dLUC) for growing biofuel feedstocks, or by the indirect land requirements (iLUC) that compensate for the diversion of food/feed crops into biofuels, both cases leading to greenhouse gas emissions. We investigated data over the last 20-year period to estimate the magnitude of the effects ethanol production in the USA has had on land use domestically and abroad. The data analyzed suggests that, over the period, the use of corn for ethanol increased by 118 Mt per year, most of it coming from displacement of other uses of corn, mainly feed, which were compensated by increased feed production elsewhere. Results suggest a relatively low dLUC but a significant iLUC effect, mainly due to the compensation for the foregone feed production as a result of diverting corn into ethanol production. The resulting 18.0 Mt CO2-eq. associated with meeting the renewable-energy target of 15 billion gallons of corn ethanol more than negates the climate benefits from avoided use of gasoline, indicating that promoting corn ethanol for global climate change mitigation may be counter-productive as, despite decreasing domestic emissions, global emissions increase. We suggest that the policy be revised accordingly.

Life cycle assessment, quo vadis? Supporting or deterring greenwashing? A survey of practitioners

“…the methodological choices made) very often stem from, and start with, the first step (goal and scope definition) which determines key decisions such as whether an attributional or consequential approach is taken and thereby how co-production is handled, 13 which in turn determines the delimitation of the system boundary. 14 LCIA characterization models are also selected during this step, and can lead to even more variability in results, 15 since impact assessment models determine the category indicators used to represent impacts and the cause-effect chains used to determine those indicators.…”