Imperial College London
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DrGonzaloGuillén-Gosálbez

Faculty of Engineering, Department of Chemical Engineering

Visiting Professor
 
 
 
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Contact

 

g.guillen05

 
 
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Location

 

ACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Ewertowska:2017:10.1016/j.jclepro.2017.07.215,
author = {Ewertowska, A and Pozo, C and Gavalda, J and Jimenez, L and Guillen-Gosalbez, G},
doi = {10.1016/j.jclepro.2017.07.215},
journal = {Journal of Cleaner Production},
pages = {771--783},
title = {Combined use of life cycle assessment, data envelopment analysis and Monte Carlo simulation for quantifying environmental efficiencies under uncertainty},
url = {http://dx.doi.org/10.1016/j.jclepro.2017.07.215},
volume = {166},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Ewertowska,A
AU  - Pozo,C
AU  - Gavalda,J
AU  - Jimenez,L
AU  - Guillen-Gosalbez,G
DO  - 10.1016/j.jclepro.2017.07.215
EP  - 783
PY  - 2017///
SN  - 0959-6526
SP  - 771
TI  - Combined use of life cycle assessment, data envelopment analysis and Monte Carlo simulation for quantifying environmental efficiencies under uncertainty
T2  - Journal of Cleaner Production
UR  - http://dx.doi.org/10.1016/j.jclepro.2017.07.215
VL  - 166
ER  -
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