Urban Science

Our Vision of Urban Science Research

Imagine a city that consumes 50 percent less total energy per person while improving economic vitality and quality of life and increasing resilience and sustainability.

Cities are responsible for 60 percent to 80 percent of the world's energy consumption. With city populations expected to rise from 3.5 billion today to 5 billion by 2030, energy and infrastructure choices made in the intervening years will define the difference between strong and stable urban spaces and crumbling infrastructure unable to serve our competitive needs.

In the U.S., more than two-thirds of the population lives in urban areas. Our cities are trying to manage growth and build for resilience, while much of America's aging urban infrastructure — including buildings, transmission systems, gas pipelines and the electricity grid — will soon need to be repaired or replaced.

Urban systems are interconnected systems of buildings, microclimate, transportation, power and water supply, and humans. Urban systems research offers insights into urban efficiency, sustainability, and resilience, leveraging emerging opportunities in IoT, big data, machine learning, and exascale computing.

Objectives

The objectives of the Urban Systems Group at Lawrence Berkeley National Laboratory (Berkeley Lab) are:

  • Bringing science solutions to urban systems using interdisciplinary approaches
  • Use data and computational tools to optimize urban system performance integrating buildings, urban climate, transportation, and socio-economics
  • Conduct applied research to support urban energy and environmental goals at the city, state and federal governments
  • Inform urban planning, policy making and evaluation
  • Integrate and coordinate Berkeley Lab resources for emerging and larger opportunities across divisions and areas
  • Partnership and collaboration with key researchers, stakeholders, cities and utilities

Research Background

The existing computational tools provide limited technical strategies and fail to use open standards that are critical for energy modeling communities to embrace. Cities need dramatically improved analytics-based decision analysis tools that combine measured data, physics- and data-driven models to support their new development and retrofit planning.

The most efficient and sustainable low-greenhouse gas and -energy systems are found in campus and urban district shared energy infrastructure that enables waste-heat recovery and integrates renewables, and thermal storage to offset fluctuations in energy demand and supply. Designing and operating such systems requires dynamic simulation and optimization to account for the dynamics of energy systems, changing loads and temperature levels, uncertainty and variability of weather and user behavior, and analysis of different design and operational scenarios. When hundreds of buildings are involved, integration of these computations with geographical information system to obtain input data and to visualize results in a form that is accessible to urban planners and designers is needed.

In an urban area, buildings release heat to the urban environment causing its temperature to rise, which leads to increased cooling loads in buildings and thus more heat emissions from building to ambient, forming close-loop interactions. Modeling such interactions between buildings and urban microclimate is key to assessing risk and evaluating technologies and strategies to reduce impacts of extreme weather events (e.g., heatwaves) on urban building operation and human health.

A model of the interactions between buildings and urban microclimates.

The sum of interactions between buildings and urban microclimates.
(Credit: The Urban Systems Group)