Thermodynamic metrics for aggregation of natural resources in life cycle analysis: insight via application to some transportation fuels.
While methods for aggregating emissions are widely used and standardized in life cycle assessment (LCA), there is little agreement about methods for aggregating natural resources for obtaining interpretable metrics. Thermodynamic methods have been suggested including energy, exergy, and emergy analyses. This work provides insight into the nature of thermodynamic aggregation, including assumptions about substitutability between resources and loss of detailed information about the data being combined. Methods considered include calorific value or energy, industrial cumulative exergy consumption (ICEC) and its variations, and ecological cumulative exergy consumption (ECEC) or emergy. A hierarchy of metrics is proposed that spans the range from detailed data to aggregate metrics. At the fine scale, detailed data can help identify resources to whose depletion the selected product is most vulnerable. At the coarse scale, new insight is provided about thermodynamic aggregation methods. Among these, energy analysis is appropriate only for products that rely primarily on fossil fuels, and it cannot provide a useful indication of renewability. Exergy-based methods can provide results similar to energy analysis by including only nonrenewable fuels but can also account for materials use and provide a renewability index. However, ICEC and its variations do not address substitutability between resources, causing its results to be dominated by dilute and low-quality resources such as sunlight. The use of monetary values to account for substitutability does not consider many ecological resources and may not be appropriate for the analysis of emerging products. ECEC or emergy explicitly considers substitutability and resource quality and provides more intuitive results but is plagued by data gaps and uncertainties. This insight is illustrated via application to the life cycles of gasoline, diesel, corn ethanol, and soybean biodiesel. Here, aggregate metrics reveal the dilemma facing the choice of fuels: high return on investment versus high renewability.
Baral
Anil
A
William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio 43210, USA.
Bakshi
Bhavik R
BR
D004784:Environmental Monitoring / Q000379:methods; D005579:Fossil Fuels; D008956:Models, Chemical; D013816:Thermodynamics; D013997:Time Factors; D001335:Vehicle Emissions / Q000032:analysis*
D005579:Fossil Fuels; D001335:Vehicle Emissions