Project 2.7 - Energy Efficiency Through Community Design

Objective
To determine how best to incorporate narrow streets and shade trees into the designs of low-income single-family housing developments to reduce ambient temperature.

Prior Research

• According to the U.S. Department of Energy report, "Landscaping for Energy Efficiency", careful landscaping can save up to 25% of a household's energy consumption for heating and cooling.
• While trees around houses can reduce cooling energy consumption by direct shading of houses, street trees reduce cooling energy consumption by reducing the surrounding ambient air temperature. The unshaded dark surface of a street acts as heat storage, absorbing heat during the day and releasing it in the afternoon and evening. A substantial tree canopy can directly shade paved surfaces. Such shading, in combination with evapo-transpiration, can significantly reduce ambient temperatures, thus reducing overall cooling energy requirements for a neighborhood. The effects of tree shading depend on the width of the street. The narrower the street, the greater the percentage of surface area that can be shaded and the sooner maximum shade tree coverage can be attained. Studies (Akbari, 1995; Sailor et al., 1992) have produced estimates that as much as 10% of urban peak electric demand is the result of the heat island effect. Studies have reported a temperature difference of up to 8°F between areas with high tree canopy and areas with no trees.

Task List

• Select Housing Developments
• Prepare Monitoring Plan
• Install Monitoring Equipment
• Data Collection
• Develop Database
• Data Analysis and Algorithm Development

Projected Outcomes

• Use collected data to establish empirical relationships showing how tree canopy and street width affect ambient temperature in a neighborhood. Prepare an empirically validated model for showing how such changes in community design as narrowing streets and providing tree canopy affect the ambient temperature for a neighborhood. Fourier series model equations are used to model the hourly data.

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