On the feasibility of using emergy analysis as a source of benchmarking criteria through data envelopment analysis: A case study for wind energy

The definition of criteria for the benchmarking of similar entities is often a critical issue in analytical studies because of the multiplicity of criteria susceptible to be taken into account. This issue can be aggravated by the need to handle multiple data for multiple facilities. This article presents a methodological framework, named the Em. +. DEA method, which combines emergy analysis with Data Envelopment Analysis (DEA) for the ecocentric benchmarking of multiple resembling entities (i.e., multiple decision making units or DMUs). Provided that the life-cycle inventories of these DMUs are available, an emergy analysis is performed through the computation of seven different indicators, which refer to the use of fossil, metal, mineral, nuclear, renewable energy, water and land resources. These independent emergy values are then implemented as inputs for DEA computation, thus providing operational emergy-based efficiency scores and, for the inefficient DMUs, target emergy flows (i.e., feasible emergy benchmarks that would turn inefficient DMUs into efficient). The use of the Em. +. DEA method is exemplified through a case study of wind energy farms. The potential use of CED (cumulative energy demand) and CExD (cumulative exergy demand) indicators as alternative benchmarking criteria to emergy is discussed. The combined use of emergy analysis with DEA is proven to be a valid methodological approach to provide benchmarks oriented towards the optimisation of the life-cycle performance of a set of multiple similar facilities, not being limited to the operational traits of the assessed units.