The environmental impact of a final product can be regarded as the sum of the impacts of all processes needed to obtain it. The impacts of these processes in all individual layers of production can be quantified using contribution analysis methods. SPA is an advanced method used to identify the chain of production processes linking the most highly emitting process with the final product. This analysis was performed in Matlab, using a specialized algorithm developed by Peters and Hertwich in 1996. In this thesis we test an interdisciplinary approach combining LCA and operational research methods for doing a SPA. A mixed integer program was developed and implemented in Gams. The performance of this generalized algorithm was benchmarked against the specialized algorithm for three test cases performed on three databases of increasing complexity. The results suggest the advantage of this algorithm in performing analysis on sparse data systems compared with the classic method involving Matlab. However, Matlabs specialized algorithm performs better for dense data systems. Many of the requirements and limitations imposed by the software involved in different steps have proved manageable. This study proves that mathematical programming can be a very useful tool for contribution analysis in general and SPA in particular.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ntnu-9982 |
| Date | January 2009 |
| Creators | Vlad, Monica |
| Publisher | Norges teknisk-naturvitenskapelige universitet, Institutt for energi- og prosessteknikk, Institutt for energi- og prosessteknikk |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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