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Journal Article

Improved exergetic life cycle assessment through matrix reduction technique

Abstract

Purpose

The concept of exergy can be used in LCA to quantify the value of natural resources consumed in production processes, as well as to assess the environmental impacts of waste streams. Prior studies noted the complexity of exergy accounting for wastes due to the diversity and complexity of waste streams. We develop an improved method to allow for rigorous exergy accounting of both resources and wastes.

Methods

The exergy content of a mass stream depends on many physical characteristics, including temperature, pressure, and chemical composition. We develop a novel matrix reduction technique to reduce data gathering requirements by multiple orders of magnitude. This method predivides the impact matrix into key rows and processes and “rest of economy” flows. Thermodynamic data can then be gathered for key flows emitted by key processes, and all other flows can be modeled using default values with little loss of accuracy.

Results and discussion

Our method is applied to an example LCA of electricity production via a natural gas combined cycle (NGCC) system. The case study finds that life cycle (economy-wide) exergetic efficiency of NGCC electricity production is ≈43 %, compared to a plant-level (local) exergetic efficiency of ≈54 %. The exergy content of life cycle waste flows is contained primarily in chemical exergy and physical exergy of flue gases, with nearly equal contributions. These waste exergy fluxes represent ≈3 % each of total input exergy.

Conclusions

The matrix reduction technique is found to be robust to assumptions about flows that are not directly modeled. By examining ranges of reasonable assumptions about mass flows not specifically modeled, we show that key rows and processes account for the vast majority of exergy content of interventions.

Author(s)
Stuart Sweeney Smith
Adelaide Calbry-Mzyka
Adam R. Brandt
Journal Name
The International Journal of Life Cycle Assessment
Publication Date
April 28, 2016
DOI
10.1007/s11367-016-1118-5
Publisher
Elsevier