Combined use of life cycle assessment, data envelopment analysis and Monte Carlo simulation for quantifying environmental efficiencies under uncertainty. (10th November 2017)

• Record Type: Journal Article
• Authors: Ewertowska, A.; Pozo, C.; Gavaldà, J.; Jiménez, L.; Guillén-Gosálbez, G.
• Is Part Of: Journal of cleaner production. Volume 166(2017)
• Page Start: 771
• Page End: 783
• Publication Date: 2017-11-10
• Subjects: Uncertainty -- Energy assessment -- Data envelopment analysis -- Life cycle assessment -- Monte Carlo simulation -- Pedigree matrix; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2017.07.215
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: The combined use of data envelopment analysis (DEA) and life cycle assessment (LCA) has recently emerged as a suitable technique for assessing the environmental efficiency of products. The standard approach DEA + LCA requires the input/output data to be perfectly known in advance. In practice, however, the environmental impact calculations are typically affected by a high degree of uncertainty stemming from lack of data and/or inaccurate measurements. This contribution introduces a methodology that combines DEA, LCA and stochastic modelling to evaluate the environmental efficiency of products under uncertainty. The capabilities of this approach are illustrated through its application to the assessment of eleven technologies for electricity generation. We show that the efficiency scores in the nominal and the stochastic cases can differ significantly, to the point that a technology can be deemed efficient or inefficient depending on the values of the uncertain parameters. These results support the need to incorporate uncertainty modeling into the DEA + LCA framework in order to further assess the validity of the deterministic calculations. Graphical abstract: Image 1 Highlights: We analyse the eco-efficiency of technologies under uncertainty. Our approach combines stochastic modelling, data envelopment analysis and life cycle assessment. The deterministic DEA results can differ significantly from the stochastic ones. Our approach underlies the need to incorporate uncertainties in environmental and eco-efficiency analysis.