CAREER: Urban Informatics for Smart, Sustainable Cities: Toward a Data-Driven Understanding of Metropolitan Energy Dynamics

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CBET 1653772; PI: Kontokosta, Constantine E. This project will use data-driven methodologies to advance fundamental understanding of urban energy dynamics through a coupled model of urban energy demand, behavior, and infrastructure. The work seeks to maximize impact by supporting evidenced-based urban energy policy, public and private decision-making, and infrastructure investment to more effectively design, implement, and evaluate energy reduction strategies. Using a diverse, comprehensive, and unique collection of data acquired by the PI, the research aims to tackle the following: (1) What drives energy use within and across cities? (2) What are the socio-technical dynamics of building energy consumption? (3) How and why do energy conservation measures and retrofit opportunities vary by building type, city, and region? (4) What are the spatial-temporal patterns of energy use in cities? (5) How do urban and regional policies impact energy efficiency and cost savings over time?The work in urban informatics and metropolitan energy dynamics is focused on developing new analytical approaches, coupled with an array of building, land use, and energy data from U.S. and international cities, to advance the fundamental understanding of the patterns and determinants of urban energy demand and GHG emissions from the built environment and their impacts on human well-being. This will be achieved by integrating methods from civil and systems engineering, data science, and computational social science to develop data-driven models to support decision-making through the extraction of actionable intelligence from big data. This research will (1) integrate an array of building, neighborhood, and city level data across tens of thousands of buildings and multiple cities, (2) utilize new sources of urban energy data to create a large, non-self-selected dataset, and (3) simultaneously examine physical, environmental, social, and behavioral components of urban dynamics to create a multi-scalar model of energy demand and reduction potentials across metropolitan areas. The research seeks to provide the analytical rigor to support objective, evidenced-based policies that will create a framework for performance-driven evaluation of proposed and implemented strategies. The education plan will facilitate development of a network of students trained in building energy efficiency, urban informatics, and urban sustainability, as well as foster greater public awareness of the scale and importance of addressing energy challenges in cities. The research and education activities will build on an existing relationship with city agencies, industry collaborators, and the MetroLab Network - a group of 34 city-university partnerships focused on data solutions to urban challenges - to provide the foundation for smart, sustainable cities in the U.S. and globally.