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01-04-2014 | LCI METHODOLOGY AND DATABASES | Issue 4/2014 Open Access

The International Journal of Life Cycle Assessment 4/2014

The ESPA (Enhanced Structural Path Analysis) method: a solution to an implementation challenge for dynamic life cycle assessment studies

Journal:
The International Journal of Life Cycle Assessment > Issue 4/2014
Authors:
Didier Beloin-Saint-Pierre, Reinout Heijungs, Isabelle Blanc
Important notes
Responsible editor: Hans-Jörg Althaus

Electronic supplementary material

The online version of this article (doi:10.​1007/​s11367-014-0710-9) contains supplementary material, which is available to authorized users.

Abstract

Purpose

By analyzing the latest developments in the dynamic life cycle assessment (DLCA) methodology, we identify an implementation challenge with the management of new temporal information to describe each system we might want to model. To address this problem, we propose a new method to differentiate elementary and process flows on a temporal level, and explain how it can generate temporally differentiated life cycle inventories (LCI), which are necessary inputs for dynamic impact assessment methods.

Methods

First, an analysis of recent DLCA studies is used to identify the relevant temporal characteristics for an LCI. Then, we explain the implementation challenge of handling additional temporal information to describe processes in life cycle assessment (LCA) databases. Finally, a new format of temporal description is proposed to minimize the current implementation problem for DLCA studies.

Results and discussion

A new format of process-relative temporal distributions is proposed to obtain a temporal differentiation of LCA database information (elementary flows and product flows). A new LCI calculation method is also proposed since the new format for temporal description is not compatible with the traditional LCI calculation method. Description of the requirements and limits for this new method, named enhanced structural path analysis (ESPA), is also presented. To conclude the description of the ESPA method, we illustrate its use in a strategically chosen scenario. The use of the proposed ESPA method for this scenario reveals the need for the LCA community to reach an agreement on common temporal differentiation strategies for future DLCA studies.

Conclusions

We propose the ESPA method to obtain temporally differentiated LCIs, which should then require less implementation effort for the system-modeling step (LCA database definition), even if such concepts cannot be applied to every process.

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Supplementary Material
ESM 1 (DOCX 91 kb)
11367_2014_710_MOESM1_ESM.docx
Literature
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