I am a research assistant in the Green Design Institute and the Center for Climate and Energy Decision Making where I develop analytical tools to better understand the climate implications of transitions between competing forms of energy (e.g., from coal to more natural gas, or from gasoline to more biofuels). I am generally interested in analyzing the key processes and parameters in a decision-making context of a complex techno-economic system, and making them transparent to decision-makers. A main feature of my work — and a great personal motivation — is bridging different research disciplines whose joined expertise has the potential to answer important research questions, which are very difficult to solve individually. Most of my research experience lies in the interactions between energy use and climate impacts, particularly with respect to transportation fuels as well as coal and natural gas.
I have 5 years of graduate research and consulting experience in renewable energy and the automotive industry in the U.S. and Germany. I received B.S. (Mechanical Engineering, 2004) and M.S. (Technology Management, 2009) equivalent degrees from the University of Stuttgart, Germany. Please see the links above for a more detailed resume including awards and a list of publications.
Two underlying questions for most of my research are: (1) how is global climate affected over time by potential transitions in the energy system? (2) How uncertain are these effects? A current example is the increasing interest in natural gas due to the exploration of new reservoirs in the U.S, which may replace significant portions of coal in the future. Life cycle assessment (LCA) is a tool that helps me study energy-climate interactions. Traditionally, LCA is used to estimate the environmental performance of competing technologies from “cradle to grave”. Policy-makers rely increasingly on LCA to support complex climate performance evaluations of emerging technologies as a means to judge its compliance with national climate mitigation targets. This is achieved by using LCA to estimate and compare the greenhouse gas (GHG) emissions of two or more competing technologies. However, interpreting LCA results based on life cycle GHG emissions is difficult for two reasons. First, anthropogenic climate change is the result of a complex process chain leading from GHG release to time-dependent changes in atmospheric GHG concentration, radiative forcing (RF), and global temperatures accompanied by nonlinear climate feedbacks. Therefore, total GHG emissions, as estimated during LCA, is only a first-order proxy for climate impacts of a given technology. My work extends traditional LCA by establishing energy transition scenarios over time based on LCA GHG inventories of specific technologies, and modeling RF and temperature changes using models developed in the climate science community.
Second, GHG emissions as well as the climate response is uncertain due to a lack of emissions data and a limited understanding of the global climate. I am interested in quantifying this uncertainty as much as possible, and applying this data to probabilistic models in order to communicate how data variability and lack of knowledge may affect the climate outcome of a specific decision (e.g., a policy to promote a specific energy transition). A particular ongoing research project investigates how atmospheric methane concentration measurements can be used to reduce uncertainty in LCA estimates of methane leakage during natural gas production.
Last updated: April 2012
Engineering and Public Policy
Baker Hall 129
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213
Dept. of Engineering and Public Policy
sschwiet [at] andrew [dot] cmu [dot] edu