If human societies are to address climate change by reducing greenhouse gas emissions, they must better understand the pathways by which transformative technologies become significant components of mainstream energy systems. Currently the primary tools for modelling the potential adoption and effects of new technologies are called integrated assessment models (IAMs). As of now, IAM representations of technological change are incomplete: while they include robust representations of certain economic factors, they do not include institutional, behavioral and social factors. Studies of technological change suggest that all of these these are fundamentally important to technology adoption and use.
This research seeks to develop better representations of non-economic drivers of technological change in energy transformations. The investigators will begin with camparative case studies involving two large-scale energy technologies (ethanol and nuclear power) in three countries (Brazil, Sweden, and the United States). The remainder of the work combines theory, field investigation, and modeling with the goal of developing improved, more valid IAMs. Improved projections of technology diffusion for climate change mitigation could help both the private sector and policymakers design more effective mitigation policies and implementation strategies.
