Background analysis of the quality of the energy data to be considered for the European Reference Life Cycle Database (ELCD)

Simone Fazio (Editor)
Marco Recchioni (Editor)
Fabrice Mathieux (Editor)
Daniel Garrain (Author)
Cristina de la Rùa (Author)
Yolanda Lechòn (Author)
Policies and Targets
Technology and Standards
Energy Generation and Distribution


The European Reference Life-Cycle Database (ELCD) has been developed by the European Commission’s Joint Research Centre (DG JRC) and provides core Life Cycle Inventory (LCI) data from front-running EU-level business associations and, where not available, other sources. Within the ELCD, several energy-related data are provided, being energy a major input for almost all the environmental analyses of products or processes. The present document summarizes an analysis of the quality of energy data for European markets that are available in 3rd party life cycle databases and from authoritative sources that are, or could be, used in the context of the ELCD. This work has been carried out by the Energy Systems Analysis (ASE) Unit of CIEMAT (Public Research Centre for Energy, Environment and Technology, Madrid, Spain), through a service contract (Service Contract Number 387533) awarded by the European Commission – Joint Research Centre – Institute for Environment and Sustainability (Tender Number IES/H/2011/01/13/NC).


The work consisted of an analysis and a comparison of energy datasets from several relevant databases (i.e. Ecoinvent[1], E3[2], and GEMIS[3]), considering the ELCD database as the basis for this analysis in order to figure out the possibilities for improvement of the ELCD overall data quality.

The current ELCD energy datasets have been to a large extent originated from the GaBi[4] database. Therefore, in order to analyse background information of the ELCD datasets, GaBi datasets from the last updated version (at the time when the study was initiated, i.e. 2009) have been analysed.

The main criteria for the other database selection were based on the availability of EU-related data, the inclusion of wide datasets on energy products and services (specially focusing on those matching the chosen energy patterns), and the broad approval by the scientific community.

24 energy datasets were chosen for the analysis with the aim of selecting a sufficiently representative sample of energy sources in the European context.

The evaluation has been based on the quality indicators developed within the ILCD handbook (EC-JRC-IES 2010a, 2010b, 2011): Technological representativeness, Geographical representativeness, Time-related representativeness, Completeness, Precision / Uncertainty, and Methodological appropriateness and consistency. These quality indicators have been refined in order to appropriately identify key aspects that are involved in both quality and methodological aspects of energy related LCI datasets. This refinement facilitates their use in the analysis of energy systems.

The quality of each dataset has been estimated for each indicator and then, compared among the different databases. Even though the final results are discussed based on “qualitative” results for each indicator, the individual indicator component and the total DQR have been calculated as a tool for further dataset improvements.


Results have shown that, in general terms the ELCD dataset analysed showed a very good performance in many of the identified quality criteria and especially in those criteria related to technology representativeness, methodology and Completeness.

Several aspects where improvements are considered necessary are highlighted through the analysis. For example, sources of data and information coming from authoritative sources, business associations or other sources are identified and proposed to be used.

One of the most relevant improvement opportunity of the ELCD is the lack of datasets that model electricity produced by each technology in each European country. Currently, the ELCD includes electricity mix datasets for each country, modelled considering an established share of sources that might be different to the needs of the user.

Although the optimal solution to this limitation would be to model new datasets for electricity production by technology and for each country, this might not be feasible for the short term. An alternative solution would be to model datasets for each technology under a European context, and to introduce parameters in the electricity mix datasets to vary the shares of each technology.

In order to give response to any change or advance in technologies, and to be able to model new datasets and/or to modify the current ones if necessary, it is highly recommended to constantly review the evolution of advanced technologies and their share in the European market..

Business associations and other authoritative sources are considered relevant sources to update the status of these technologies. Along this study relevant sources have been identified.



The future versions of the ELCD should include new datasets for electricity production by technology and by country. Also, future electricity scenarios can be developed using to that end the output from reference energy models, developed by the European Commission at different levels, such as PRIMES[5] or TIMES[6]. This is an important improvement of the database that could be very useful for prospective and consequential LCA studies.

Modelling the end of life of the energy systems appears to be a difficult task due to the novelty of some technologies and the lack of data from other technologies (solar PV, final repository for spent nuclear fuel and natural gas plant dismantling). Efforts on this challenge should be kept in the future.

Finally, deep analysis of the learning curves is recommended to identify the level of maturity for each technology. Then, special periods for reviewing could be identified by technology.
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