Simultaneous allocation and data reconciliation procedure in life cycle inventory analysis using fuzzy mathematical programming
Life cycle assessment (LCA) is a methodology used in assessing the environmental impacts of products. Life cycle inventory analysis (LCI) is one of the four components of LCA which quantifies flows of materials and pollutants in the entire life cycle (cradle-to-grave) of the product. Data are common...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | text |
| Published: |
Animo Repository
2011
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/1584 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Summary: | Life cycle assessment (LCA) is a methodology used in assessing the environmental impacts of products. Life cycle inventory analysis (LCI) is one of the four components of LCA which quantifies flows of materials and pollutants in the entire life cycle (cradle-to-grave) of the product. Data are commonly collected from various sources (e.g. publications, databases and site-specific measurements) which may result in violations of mass and energy balances due to uncertainties. In such cases, the data can be adjusted using reconciliation methods to improve the reliability of the results. Another computational issue in LCI arises when two or more products are involved, known as the multi-functionality or allocation problem. The problem is how to allocate resource and emission streams to each product. This work describes a model using fuzzy optimization for solving both allocation and data reconciliation problems simultaneously. The model is illustrated on an aluminum industry case study involving open-loop recycling, and the approach is compared with two sequential allocation and data reconciliation methods. Copyright © 2010 Curtin University of Technology and John Wiley & Sons, Ltd. |
|---|