Evaluating Biomass Energy Policy in the Face of Emissions Reductions Uncertainty and Feedstock Supply Risk

• Main Author: Mullins, Kimberley A.
• Format: Others
• Published: Research Showcase @ CMU 2012
• Subjects: Civil and Environmental Engineering
• Online Access: http://repository.cmu.edu/dissertations/130; http://repository.cmu.edu/cgi/viewcontent.cgi?article=1133&context=dissertations

Biofuels have received legislative support recently in California’s Low-Carbon Fuel Standard and the Federal Energy Independence and Security Act. Both discuss new fuel types, but neither provides methodological guidelines for dealing with the inherent uncertainty in evaluating their potential life-cycle greenhouse gas emissions. Emissions reductions are based on point estimates only. This work develops a Monte Carlo simulation to estimate life-cycle emissions distributions from ethanol and butanol from corn or switchgrass. Life-cycle emissions distributions for each of the modelled feedstock and fuel pairings span an order of magnitude or more. Corn ethanol emissions range from 50 to 200 g CO2e/MJ, and each feedstock-fuel pathway studied shows some probability of greater emissions than a distribution for gasoline. Potential GHG emissions reductions from displacing fossil fuels with biofuels are difficult to forecast given this high degree of uncertainty in life-cycle emissions. Incorporating uncertainty in the decision making process can illuminate the risks of policy failure (e.g., increased emissions), and a calculated risk of failure due to uncertainty can be used to inform more appropriate reduction targets in future biofuel policies. The current practice of modelling cellulosic biomass yields based on point values that have been aggregated over space and over time conceal important energy supply risks related to depending on biomass for transportation energy, particularly those related to local drought conditions. Using switchgrass as a case study, this work quantifies the variability in expected yields over time and space with a switchgrass growth model and historical weather data. Even with stable, productive states, yields vary from 5 to 20 Mg/ha. Yields are likely to be reduced with increased temperatures and weather variability induced by climate change. Thus, variability needs to be a central part of biomass systems modelling so that risks to energy supplies are acknowledged and risk mitigation strategies or contingency plans are considered. Irrigation, a potential risk mitigation strategy, can very often negate the impacts of drought, although system-wide irrigation is an expensive method to stabilize crops (costing $0.10 to $1.90/gallon). Unless many surplus acres of cellulosic crops are planted, there will be insufficient ethanol to meet the EISA targets 10 to 25% of the time under rain-fed conditions. Thinking in terms of yield ranges, not point estimates, is essential in planning a long-term energy system dependent on biomass.