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Parameter variation and scenario analysis in impact assessments of emerging energy technologies

Abstract

There is a global need for energy technologies that reduce the adverse impacts of societal progress and that address today's challenges without creating tomorrow's problems. Life cycle impact assessment (LCIA) can support technology developers in achieving these prerequisites of sustainability by providing a systems perspective. However, modeling the early-stage scale up and impacts of technology systems may lead to unreliable or incomplete results due to a lack of representative technical, spatial, and temporal data. The goal of this dissertation is to support the acceleration of clean energy technology development by providing information about the regional variation of impacts and benefits resulting from plausible deployment scenarios. Three emerging energy technologies are selected as case studies: (1) brine management for carbon dioxide sequestration; (2) carbon dioxide capture, utilization, and sequestration; (3) stationary fuel cells for combined heat and power in commercial buildings. In all three case studies, priority areas are identified where more reliable data and models are necessary for reducing uncertainty, and vital information is revealed on how impacts vary spatially and temporally. Importantly, moving away from default technology and waste management hierarchies as a source of data fosters goal-driven systems thinking which in turn leads to the discovery of technology improvement potentials.

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