@proceedings{22858,
  keywords = {China, China Energy Group, China Energy, Energy Analysis and Environmental Impacts Division, International Energy Department, Low-Carbon Eco-City Development, Energy consumption, Urban rapidassessment model},
  author = {David Fridley and Nina Zheng and Nan Zhou and Nina Khanna},
  title = {Urban RAM: Assessing the Energy Impact of Having People in Cities},
  abstract = {<p>"Low Carbon Cities" is a concept that has primarily focused on ways to reduce the impacts of current energy consumption in transportation and buildings. What is often overlooked as part of the energy impact of urban areas is the built space itself—the streets, pavement, buildings, etc.—that are required to maintain such a dense arrangement of humans, and the energy used to manufacture, transport, and sell the consumption goods and services that urban residents purchase. A new model—the Urban Rapid Assessment Model (Urban RAM)—was built to provide a high-level breakdown of the major contributors to a given city's energy and carbon footprint when measured from the point of view of that city's inhabitants and their activities. By allocating both embodied and operational energy consumption to the various functions of city residents, such as living, commuting, shopping, or working, it is possible to understand better the drivers of urban emissions growth and areas of possible policy intervention.Urban RAM was applied to a case study of Suzhou, a city of 6 million near Shanghai. The model calculated a total annual energy footprint of ~111 billion MJ, of which three-quarters is energy embodied in the city's infrastructure and goods and services consumption and the other 26% is operational energy. Of the embodied energy, nearly 80% came from goods and services that city residents consume each year, of which nearly half came from food and nearly one-quarter embodied in the clothing. Transportation dominated operational energy with 59% and residential buildings with 26%.</p>},
  year = {2012},
  journal = {ACEEE Summer Study on Energy Efficiency in Buildings},
  month = {06/2012},
  publisher = {American Council for an Energy-Efficient Economy},
  address = {Pacific Grove, California, U.S.A.},
  url = {http://aceee.org/files/proceedings/2012/data/papers/0193-000350.pdf#page=1},
}