| Title |
Background qualitative analysis of the European Reference Life Cycle Database (ELCD) energy datasets – part I: fuel datasets
|
|---|---|
| Published in |
SpringerPlus, March 2015
|
| DOI | 10.1186/s40064-015-0915-9 |
| Pubmed ID | |
| Authors |
Daniel Garraín, Simone Fazio, Cristina de la Rúa, Marco Recchioni, Yolanda Lechón, Fabrice Mathieux |
| Abstract |
The aim of this study is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) fuel datasets. 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. 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. 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. |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 22% |
| Student > Ph. D. Student | 6 | 16% |
| Other | 4 | 11% |
| Student > Doctoral Student | 4 | 11% |
| Student > Master | 4 | 11% |
| Other | 3 | 8% |
| Unknown | 8 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 7 | 19% |
| Agricultural and Biological Sciences | 4 | 11% |
| Chemical Engineering | 3 | 8% |
| Engineering | 3 | 8% |
| Business, Management and Accounting | 1 | 3% |
| Other | 5 | 14% |
| Unknown | 14 | 38% |