Recently, algae have received a significant amount of attention as a potential feedstock for alternative fuels. Although multiple fuels have been proposed that would use algae as a feedstock, the most commonly explored algae-based alternative fuel is biodiesel. There are several coarse estimates that quantify the potential of algae as a feedstock for biodiesel. Some of these analyses have not incorporated specific values of algal lipid content and did not include processing inefficiencies. For example, in some analyses, specificity to the algal species and growth conditions is not provided, thereby introducing the opportunity for error. In addition, all necessary processing steps required for biodiesel production and their associated energy, materials, and costs might not be included. The accuracy associated with these estimates can be improved by using data that are more specific, including all relevant information for biodiesel production, and by presenting information with more relevant metrics. In order to determine whether algae are a viable source for biodiesel, two questions must be answered: 1) how much biodiesel can be produced from algae, and 2) what is the cost of production? To accurately answer these questions, we propose a framework for characterizing biodiesel production from algae. The framework focuses on three main principles. The first principle is the need for results to be presented in strong metrics. The strength of a metric is dependent upon the amount of information that it represents. The second principle in the proposed framework is that we suggest that researchers leave unknown information in symbolic form in order to present results in strong metrics. Presenting results in this manner ensures that results are not taken out of context; enables primary research results to be incorporated in systems-level analyses; and specifically identifies the areas where additional research is needed. The third principle is that results should be specific (to algal species, growth conditions, and product composition) and include as much information relevant to the entire biodiesel production pathway as possible, particularly including information for the energy, materials, and cost balances. To illustrate the application of the proposed framework, several examples of strong reporting metrics are presented. In addition, the presentation of unknowns in symbolic notation, and the associated benefit, is demonstrated. Finally, the limitations of several non-specific and non-inclusive reporting metrics are presented to highlight the necessity for consistent results regarding the potential for algae as a biodiesel feedstock.

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