Abstract
Most of current life-cycle approaches show an anthropocentric standpoint for the evaluation of human-dominated activities. However, this perspective is insufficient when it comes to assessing the contribution of natural resources to production processes. In this respect, emergy analysis evaluates human-driven systems from a donor-side perspective, accounting for the environmental effort performed to make the resources available. This article presents a novel methodological framework, which combines emergy analysis and dynamic Data Envelopment Analysis (DEA) for the ecocentric assessment of multiple resembling entities over an extended period of time. The use of this approach is shown through a case study of wind energy farms. Furthermore, the results obtained are compared with those of previous studies from two different angles. On the one hand, a comparison with results from anthropocentric approaches (combined life cycle assessment and DEA) is drawn. On the other hand, results from similar ecocentric approaches, but without a dynamic model, are also subject to comparison. The combined use of emergy analysis and dynamic DEA is found to be a valid methodological framework for the computation of resource efficiency and the valuation of ecosystem services. It complements traditional anthropocentric assessments while appropriately including relevant time effects.
Highlights
The current level of extraction of primary resources—around 60 billion tons per year globally—is not sustainable [1]
These life-cycle inventory (LCI) are used to carry out the emergy analysis of each DMU for each period by using the SCALE software developed by Marvuglia et al [21]
Because the comparison is limited to efficiency scores, excluding the benchmarking of operational and environmental targets, the choice of the life cycle impact assessment method does not affect the results presented
Summary
The current level of extraction of primary resources—around 60 billion tons per year globally—is not sustainable [1]. Fundamental changes and policy measures are required in order to promote a shift in production processes, supply-chain management and consumption patterns [2,3,4]. In this sense, a dematerialization strategy should be followed, i.e., decoupling natural resource use from economic growth and social prosperity [1,2]. A dematerialization strategy should be followed, i.e., decoupling natural resource use from economic growth and social prosperity [1,2] This calls for a sustainable and efficient use of resources, security in the supply of raw materials and reduction in life-cycle environmental impacts. Within this context, novel methodological frameworks for assessing systems performance are needed to ensure the rational use of natural resources [4]
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