A Meta-Model for Life Cycle Assessment of Algae-to-Energy Systems

University Of Virginia Main Campus, Charlottesville VA

Investigators

Abstract

1067563 (Colosi). The goal of this research is to develop a meta-model of existing algae-to-energy life cycle analyses (LCAs) in order to evaluate the impact of emerging technologies in this burgeoning sector. The model will be analogous to two other widely influential energy meta-models: Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) developed for petroleum at Argonne National Lab; and ERG Biofuel Assessment Meta-Model (EBAMM) for ethanol production from the University of California at Berkeley. Both of these have become enormously useful tools for setting policy and directing engineering research. The proposed Meta-Model of Algae Bio-Energy Life Cycles (MABEL) is targeted to overcome seeming disparities among the current body of algae LCA knowledge. Many of these disparities reflect key differences in modeling strategies among authors such that standardization of functional unit, system boundaries, and key model parameters will provide more definitive estimates of energy use, greenhouse gas emissions, land use, and water use associated with energy production from algae. MABEL will facilitate more direct, data-driven comparisons among proposed algae cultivation/conversion mechanisms and between algae-derived energy and energy from terrestrial crops. The model will be open-source and freely available via download from a website hosted by the Office of the Vice President for Research at the University of Virginia (UVA). Users will be able to manipulate the model to investigate processes of interest in a flexible manner. In light of the large amount of economic and research activity that is currently being dedicated to algae-based energy, and the vigorous debate over the merits of these technologies, such a model is clearly needed by the bioenergy community. The project will compile and normalize six existing life cycle assessments into an open-source modeling platform. It will be the first open-source meta-model of the LCA impacts of algae-to-energy systems. MABEL will be stochastic so that it can capture the uncertainty inherent to this rapidly changing sector. This model will also be reconfigurable such that users will be able to use it for their own purposes. This tool will be a contribution to the industrial ecology community because it will demonstrate the usefulness of LCA as a proactive design tool. Once it is complete and fully functional, MABEL will be used by the PIs to answer key questions about algae farming, algae conversion, and algae financial considerations. The broader impact of this research will be to disseminate the MABEL platform via a freely accessible website, conference presentations, and academic publications. The model website will offer extensive documentation on policy-relevant scenarios that will be developed during this work to demonstrate the capabilities of the model and also to serve as a template for others hoping to modify the model. The project will combine the expertise of an environmental engineer and chemist with extensive experience in LCA, an environmental biochemist specializing in the environmental impacts of emerging contaminants, and a finance professor from the McIntire School of Commerce at UVa who is an expert in ecosystem services and costing models.