Critical Appraisal of Life Cycle Impact Assessment Databases for Agri‐food Materials
Bibliographic Data
| ID | 19467458 |
|---|---|
| Authors | Ricardo F M Teixeira (0000-0001-9915-6264, University of Antwerp, corresponding author) |
| Year | 2015 |
| Volume | 19 |
| Issue | 1 |
| Pages | 38-50 |
| Publication date | 2015-02-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Industrial Ecology (JOURNAL) |
| Journal identifiers | ISSN: 1088-1980 • E-ISSN: 1530-9290 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1111/jiec.12148 |
| OpenAlex | W1506202229 |
| Language | EN |
| References cited | 27 |
Simplified life cycle assessment (LCA) is an attempt to expedite standard LCA methodology. One common simplification is to use secondary databases comprised of results, instead of inventories, from previous LCA studies to avoid data collection and speed up calculations. This article contains an assessment of the depth and variance in such databases, using descriptive analyses and clustering of 2,276 published global warming potential weighted emissions records for agri‐food products. Tables with mean and standard deviation for each product were generated and can be used in the future by LCA practitioners. The analysis of the data sets shows that clustering emissions by product name explains 55% of the variance in the database, whereas geographic region and method of production of the material explain only 2%. Significant gaps in the richness and comprehensiveness of databases available are also identified; data unavailability is one of the main reasons for uncertainty. The conclusion is thus that the use of secondary databases looks promising, but there are still challenges to overcome regarding the depth of databases
Business · Cluster analysis · Data collection · Database · Economics · Global-warming potential · Greenhouse gas · Industrial ecology · Life-cycle assessment · Statistics · Sustainability · Unavailability · Agriculture Sustainability and Environmental Impact · Computer Science · Environmental Impact and Sustainability · Environmental Science · Mathematics · Sustainable Industrial Ecology · Accounting
| Highly cited | No |
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