Daniel Garraín1, Simone Fazio2, Cristina de la Rúa1, Marco Recchioni2, Yolanda Lechón1, Fabrice Mathieux2. 1. Energy Department, Energy Systems Analysis Unit, CIEMAT, Av. Complutense 40, E28040 Madrid, Spain. 2. European Commission, Joint Research Centre, Institute for Environment and Sustainability, Unit JRC.H.8-Sustainability Assessment, Via E. Fermi 2749 - TP 270, 21027 Ispra, Italy.
Abstract
INTRODUCTION: The aim of this study is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) fuel datasets. CASE DESCRIPTION: The revision is based on the data quality indicators described by the ILCD Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. DISCUSSION AND EVALUATION: Results show that ELCD fuel datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the fuel-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. CONCLUSIONS: Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD fuel datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall DQR of databases.
INTRODUCTION: The aim of this study is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) fuel datasets. CASE DESCRIPTION: The revision is based on the data quality indicators described by the ILCD Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. DISCUSSION AND EVALUATION: Results show that ELCD fuel datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the fuel-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. CONCLUSIONS: Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD fuel datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall DQR of databases.
Entities:
Keywords:
Biofuel; Data quality indicators; ELCD database; Energy datasets; Fuel; Natural gas