Jump to Main Content
Life-cycle energy implications of different residential settings: Recognizing buildings, travel, and public infrastructure
- Nichols, Brice G., Kockelman, Kara M.
- Energy Policy 2014 v.68 pp. 232-242
- petroleum, natural gas, models, suburban areas, embodied energy, population density, population growth, energy efficiency, buildings, travel, issues and policy, energy conservation, Texas
- The built environment can be used to influence travel demand, but very few studies consider the relative energy savings of such policies in context of a complex urban system. This analysis quantifies the day-to-day and embodied energy consumption of four different neighborhoods in Austin, Texas, to examine how built environment variations influence various sources of urban energy consumption. A microsimulation combines models for petroleum use (from driving) and residential and commercial power and natural gas use with rigorously measured building stock and infrastructure materials quantities (to arrive at embodied energy). Results indicate that the more suburban neighborhoods, with mostly detached single-family homes, consume up to 320% more embodied energy, 150% more operational energy, and about 160% more total life-cycle energy (per capita) than a densely developed neighborhood with mostly low-rise-apartments and duplexes. Across all neighborhoods, operational energy use comprised 83 to 92% of total energy use, and transportation sources (including personal vehicles and transit, plus street, parking structure, and sidewalk infrastructure) made up 44 to 47% of the life-cycle energy demands tallied. Energy elasticity calculations across the neighborhoods suggest that increased population density and reduced residential unit size offer greatest life-cycle energy savings per capita, by reducing both operational demands from driving and home energy use, and from less embodied energy from construction. These results provide measurable metrics for comparing different neighborhood styles and develop a framework to anticipate energy-savings from changes in the built environment versus household energy efficiency.