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Deidre Wolff School of Civil and Building Services Engineering Prof. Aidan Duffy

Comparative Analysis of Life Cycle Inventory Techniques and Development of a Quantitative Uncertainty Analysis Procedure. Deidre Wolff School of Civil and Building Services Engineering Prof. Aidan Duffy Prof. Geoff Hammond Nov. 29, 2013. Life Cycle Assessment (LCA).

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Deidre Wolff School of Civil and Building Services Engineering Prof. Aidan Duffy

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  1. Comparative Analysis of Life Cycle Inventory Techniques and Development of a Quantitative Uncertainty Analysis Procedure Deidre Wolff School of Civil and Building Services Engineering Prof. Aidan Duffy Prof. Geoff Hammond Nov. 29, 2013

  2. Life Cycle Assessment (LCA) ‘The compilation and evaluation of the inputs, outputs, and potential environmental impacts of a product system throughout its life cycle’ (ISO 14044, 2006)

  3. Life Cycle Assessment (LCA) Four Stages: • Goal and Scope Definition • Life Cycle Inventory (LCI) • Life Cycle Impact Assessment (LCIA) • Interpretation Goal Definition and Scope Inventory Analysis Interpretation Impact Assessment (ISO 14040)

  4. Motivation • LCA is often used in decision-making processes and to inform policy • LCA involves using expert judgement, assumptions, data of poor quality, allocation and weighting • These all introduce uncertainty • Uncertainty is often ignored in LCA studies due to lack of knowledge and/or time and budget constraints

  5. Objectives Conduct Process, Input-Output, and Hybrid LCA of a simple system, quantifying overall uncertainty for each model Compare the results obtained using different LCI methods Develop a technique to make comparisons between studies that have applied different LCI methods Apply methodology to a building, using a Bill of Quantities (BoQ) as a data source Determine a suitable LCI and uncertainty analysis methodology to apply to all LCA studies in the built environment

  6. What is uncertainty? Errors originating from inaccurate measurements, lack of data, and model assumptions (Huijbregts, 1998) The problem of using information that is unavailable, wrong, unreliable, or that shows a certain degree of variability (Heijungs, 2004)

  7. Uncertainty Classification in LCA • Parameter • data uncertainty • arises due to incomplete knowledge of true value of data, lack of data or measurement error • Model • unknown interactions between model formulations, due to simplification, derivation of characterization factors, aggregation of data into impact categories • Scenario • due to decisions made during the LCA, such as choice in system boundary, functional unit, allocation, weighting factors

  8. LCA Overall Steps... Goal and Scope LCI LCIA Interpretation Data Collection System Boundary Identify Significant Issues Choose Impact Categories FU and Reference Flow Contribution/ Sensitivity Analysis Scale Data to FU/ Ref Flow Characterization Factors Allocation Procedure Weighting Methods Uncertainty Analysis LCI/LCIA Method Assumptions

  9. (Reap et al, 2008)

  10. Case-study: Process LCA Goal and Scope: • Determine the overall Global Warming Potential for the production of an electric kettle, using data from EcoInvent Database. • System boundary is cradle-to-gate, including raw material extraction and manufacturing of the materials used for the production of a kettle. • The system boundary is simplified, as the overall goal of the LCA is to quantify the uncertainty.

  11. Case-study: Process LCA Energy Input Energy Input Energy Input Energy Input Transport of Electric Kettle to Consumer Raw Material Extraction Transport to production facility Assembly of Electric Kettle Energy Input Energy Input Emissions to Air Emissions to Air Emissions to Air Emissions to Air Disposal/ Recycling Use Phase Emissions to Air Emissions to Air

  12. System Diagram The emissions associated with energy consumed during these steps has been ignored for simplification Stainless Steel 437 g Poly-propylene 682.9 g 245.5 g Body of Kettle Silicone 0.4 g 1038.5 g Assembly Kettle 15 g Stainless Steel Poly-propylene 310.2 g 355.6 g Electrical Component 41.9 g Copper 3.5 g Polyamide

  13. Process LCI and LCIA Results

  14. Contribution Analysis

  15. Contribution Analysis

  16. Sensitive Parameters

  17. Sensitivity Analysis

  18. Next Steps… Quantify Uncertainty Identify scenario and model uncertainty Is it necessary to quantify scenario and model uncertainty in all cases?

  19. Thank You!Any Questions?

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