Uncertainty Quantification in Life Cycle Assessments: Interindividual Variability and Sensitivity Analysis in LCA of Air‐Conditioning Systems

12 Pages Posted: 24 Oct 2017

See all articles by Stephen A. Ross

Stephen A. Ross

Massachusetts Institute of Technology (MIT) - Sloan School of Management; Yale University - International Center for Finance

Lynette Cheah

Institute of Chemical and Engineering Sciences

Date Written: October 2017

Abstract

The life cycle environmental profile of energy‐consuming products, such as air conditioning, is dominated by the products’ use phase. Different user behavior patterns can therefore yield large differences in the results of a cradle‐to‐grave assessment. Although this variation and uncertainty is increasingly recognized, it remains often poorly characterized in life cycle assessment (LCA) studies. Today, pervasive sensing presents the opportunity to collect rich data sets and improve profiling of use‐phase parameters, in turn facilitating quantification and reduction of this uncertainty in LCA. This study examined the case of energy use in building cooling systems, focusing on global warming potential (GWP) as the impact category. In Singapore, building cooling systems or air conditioning consumes up to 37% of national electricity demand. Lack of consideration of variation in use‐phase interaction leads to the oversized designs, wasted energy, and therefore reducible GWP. Using a high‐resolution data set derived from sensor observations, energy use and behavior patterns of single‐office occupants were characterized by probabilistic distributions. The interindividual variability and use‐phase variables were propagated in a stochastic model for the life cycle of air‐conditioning systems and simulated by way of Monte Carlo analysis. Analysis of the generated uncertainties identified plausible reductions in global warming impact through modifying user interaction. Designers concerned about the environmental profile of their products or systems need better representation of the underlying variability in use‐phase data to evaluate the impact. This study suggests that data can be reliably provided and incorporated into the life cycle by proliferation of pervasive sensing, which can only continue to benefit future LCA.

Keywords: eco‐design, global warming potential, industrial ecology, Monte Carlo simulation, use‐phase, user behavior

Suggested Citation

Ross, Stephen A. and Cheah, Lynette, Uncertainty Quantification in Life Cycle Assessments: Interindividual Variability and Sensitivity Analysis in LCA of Air‐Conditioning Systems (October 2017). Journal of Industrial Ecology, Vol. 21, Issue 5, pp. 1103-1114, 2017, Available at SSRN: https://ssrn.com/abstract=3057720 or http://dx.doi.org/10.1111/jiec.12505

Stephen A. Ross (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
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Cambridge, MA 02142
United States
203-432-6015 (Phone)
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Yale University - International Center for Finance

Box 208200
New Haven, CT 06520-8200
United States

Lynette Cheah

Institute of Chemical and Engineering Sciences ( email )

1 Pesek Road
Jurong Island, 627833
Singapore

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