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Erschienen in: The International Journal of Life Cycle Assessment 3/2017

16.07.2016 | LCA FOR ENERGY SYSTEMS AND FOOD PRODUCTS

Life cycle inventories of electricity supply through the lens of data quality: exploring challenges and opportunities

verfasst von: Miguel F. Astudillo, Karin Treyer, Christian Bauer, Pierre-Olivier Pineau, Mourad Ben Amor

Erschienen in: The International Journal of Life Cycle Assessment | Ausgabe 3/2017

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Abstract

Purpose

Electricity is one of the main contributors to global environmental impacts, and its role as an energy carrier is expected to grow substantially. Consequently, reliable and accurate inventories of material and energy flows associated with electricity supply are essential in environmental assessments. This article aims to summarize existing challenges and opportunities in the modeling of life cycle inventories (LCIs) of electricity supply from a data quality perspective.

Methods

We systematically review the state-of-the-art in LCI modeling of current and future electricity supply worldwide. The analysis is structured according to the data quality characteristics proposed in ISO 14044: 2006: representativeness, completeness, consistency, reproducibility, uncertainty, data sources, and precision.

Results and discussion

Looking at existing LCIs through the lens of data quality, we observe difficulties in obtaining temporally and technologically representative data, while geographically representative data is still unavailable for some regions. Moreover, meta-analyses encountered issues of reproducibility combined with a lack of consistency across studies, impeding interstudy comparability. Additionally, some flows such as upstream fugitive emissions have been underestimated. The aforementioned issues have a negative impact on the quality of LCIs. Here, we provide recommendations on how several methods such as equilibrium models, regression, or parameterization can be used to improve data quality, underpinned by more powerful data formats. Open-source models, data platforms, as well as a list of key parameters to be reported are suggested to facilitate reproducibility and enhance transparency of electricity LCIs.

Conclusions

There are several methods and resources that can be used to improve LCIs of electricity supply, enabling more ambitious and powerful analyses. Nonetheless, special care should be taken concerning tradeoffs between different data quality aspects. For instance, more complex and accurate models may result in a loss of transparency and reproducibility unless additional reporting efforts are conducted. Other approaches, such as systematic parameterization do not compromise data quality and should be used to improve the consistency and reproducibility of inventories.

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Fußnoten
1
Consequential LCA (CLCA) accounts for changes on flows in response to decisions and attributional LCA (ALCA) quantifies flows within a chosen temporal window (Curran et al. 2005). For further clarifications, see Ekvall and Weidema (2004).
 
2
The review uses the following classification of uncertainty types: the inherent uncertainty (basic uncertainty) and uncertainty introduced by the use of imperfect data (i.e., use of data not completely representative for the context of use), here referred as epistemic uncertainty.
 
3
Power theft needs to separately accounted in LCIs and can be up to 15 % in several countries. However, many of these countries lack of the means to accurately measure electricity use at end user level. See Smith (2004) for an overview of the issue.
 
4
Because ILCD and Ecospold 2 were built around specific databases, they conform to particular needs and some differences preclude seamless transition between formats. For a review on the differences on parameterization and uncertainty modeling in Ecospold 2 and ILCD, see Cooper et al. (2012).
 
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Metadaten
Titel
Life cycle inventories of electricity supply through the lens of data quality: exploring challenges and opportunities
verfasst von
Miguel F. Astudillo
Karin Treyer
Christian Bauer
Pierre-Olivier Pineau
Mourad Ben Amor
Publikationsdatum
16.07.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
The International Journal of Life Cycle Assessment / Ausgabe 3/2017
Print ISSN: 0948-3349
Elektronische ISSN: 1614-7502
DOI
https://doi.org/10.1007/s11367-016-1163-0

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