Dr. Laura M. Arpan is the Theodore Clevenger Professor of Communication and Director of Doctoral Studies in the School of Communication at Florida State University. Dr. Arpan’s research examines risk perceptions, human motivation and responses to pro-environmental messages, interventions, and related technologies. Her projects focus on the effectiveness of promotional messages and outreach efforts designed to encourage sustainable behaviors such as energy conservation and efficiency. Recent work has examined Americans’ attitudes toward energy conservation and sustainability, factors enhancing the effectiveness of information campaign messages promoting energy-use-reduction and sustainability
Dr. Laura M. Arpan is the Theodore Clevenger Professor of Communication and Director of Doctoral Studies in the School of Communication at Florida State University. Dr. Arpan’s research examines risk perceptions, human motivation and responses to pro-environmental messages, interventions, and related technologies. Her projects focus on the effectiveness of promotional messages and outreach efforts designed to encourage sustainable behaviors such as energy conservation and efficiency. Recent work has examined Americans’ attitudes toward energy conservation and sustainability, factors enhancing the effectiveness of information campaign messages promoting energy-use-reduction and sustainability
Tianzhen Hong (LBNL) presented his research on February 6th at CURENT, University of Tennessee: “Scaling up building energy efficiency: Connecting smart cities and communities.”
February 6, 2018
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Buildings in U.S. cities consume up to 70% of primary energy. Reducing energy use in buildings becomes a key strategy for cities to achieve their energy and environmental goals. This talk will introduce on-going urban systems research at Lawrence Berkeley National Laboratory, including: (1) Integration of city's building stock and energy use data into standardized 3D city models, (2) using machine learning methods to reveal energy use patterns in buildings, (3) using exascale computing to identify, evaluate and prioritize citywide building energy retrofits, and (4) advanced district energy systems for smart cities and communities. A case study will be provided