In recent years, there has been a growing interest in comparing and benchmarking the energy use of buildings in cities. Existing frameworks such as the U.S. Environmental Protection Agency (EPA) Energy star program and the U.S. Green Building Council Leadership in Energy and Environmental Design (LEED) certification provide coarse measures of energy performance and do not fully capture specific features of the localized building stock that can influence consumption patterns. Overall performance of existing buildings in a particular municipality can be impacted by physical and occupancy characteristics, such as size, mass, age, and implemented technologies, as well as the condition and extent of supporting infrastructure and the morphology of the city. In addition, local land use and building regulations, energy policies, and socio-cultural context can be significant drivers for the adoption of energy efficient technologies and behavior. In this study, we analyze publicly available energy disclosure data from five U.S. cities, collected through local energy disclosure ordinances, in order to understand the spatial patterns of energy consumption in varying urban environments. We use data on actual annual energy consumption and physical and use characteristics for 2,250 office properties for the year 2014. This robust dataset allows us to study differences between the building stock in various municipalities, as well as to model direct building-to-building benchmarking comparisons. The objective of this research is to develop the foundation for a city-scale energy model that explains the impact of the urban built environment on energy consumption between buildings of similar type, and to create a robust, data-driven, and cross-city building energy efficiency benchmarking framework.