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Presents

A PhD Dissertation Defense

"Technological Change in the Life Cycle Assessment of Rapidly Expanding
Greenhouse Gas Mitigation Technologies: Case Studies on Thin-Film Photovoltaics and LED Lighting"

Joe Bergesen
PhD Candidate
Bren School

Tuesday, June 9, 2015
2:15 p.m.
Bren Hall 1414

Faculty Advisor: Sangwon Suh
Committee Members: Roland Geyer, Robert Deacon

Abstract
Unprecedented deployment of a wide variety of greenhouse gas mitigation technologies over the coming decades is needed to avoid the most catastrophic impacts of climate change. Many of these technologies, such as thin-film photovoltaic (PV) solar power and efficient light emitting diodes (LEDs) are still in early stages of development and are just beginning to expand into the mainstream. Assessing the long-term environmental and natural resource risks, benefits, and tradeoffs of many of these technologies using life cycle assessment (LCA) can be challenging due to their changing capabilities, costs, and resource requirements. My dissertation consists of three papers that highlight the importance of accounting for technological change in the life cycle assessment of greenhouse gas mitigation technologies.

The first article integrates LCA with technology roadmaps and electricity generation scenarios to assess the influence of both direct and economy-wide technological changes on the life cycle impacts and benefits of thin-film cadmium telluride (CdTe) and copper indium gallium selenide (CIGS) PV systems by 2030. The second article investigates how aggressive deployment of efficient LED light sources would affect the aggregate global environmental and natural resource impacts of light provision as LED technology improves and as global electricity generation is decarbonized.

Finally, technology learning curves observe reductions in costs from increased production of a technology. Traditional learning curves do not distinguish the different direct and supply-chain innovations that lead to cost reductions, or how those innovations can change the life cycle impacts of a technology. In the final article, I propose a mathematical framework for separating the different effects of learning throughout the supply chain of a technology. I use this framework to forecast the changing life cycle greenhouse gas emissions of CdTe PV power as its production is increased, and to show how technology learning in the supply chain help can contribute to empirically observed learning rates for GHG mitigation technologies.

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